Financial institution website site selection method and device and storage medium

Abstract

The invention discloses a site selection method and device of a financial institution website and a storage medium. Relates to the field of artificial intelligence, and the method comprises the steps: obtaining a pre-site selection position set, the pre-site selection position set comprises X pre-site selection positions, and X is a positive integer greater than 1; determining a service point set according to the pre-site selection position set and the existing financial institution network points; according to the pre-addressing location set and the service point set, determining a shortest route set between each pre-addressing location in the pre-addressing location set and each service point in the service point set based on a path planning algorithm; and according to the shortest route set, determining a target site selection position from the pre-site selection position set based on a P-median algorithm. According to the invention, the problem that the accuracy of website site selection is low and the rationality of website layout is influenced in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and more specifically, to a method, device and storage medium for selecting a location for a financial institution branch. Background Art

[0002] In the daily operation and business expansion of financial institutions, the location selection of outlets is a crucial decision-making link, which is directly related to the market competitiveness, customer satisfaction and overall profitability of the outlets. Traditionally, the location selection of financial institutions mainly relies on the experience judgment and field investigation of experts. Although this process takes into account the intuitive geographical location advantages and local economic conditions, it often has some limitations. Experts' evaluations are often affected by personal experience and current market conditions, and lack quantitative analysis of historical data and future trends, resulting in high subjectivity and uncertainty in location selection decisions. In addition, field investigations and expert consultations often ignore the role of big data and quantitative analysis in location selection decisions, and fail to fully consider multi-dimensional data such as traffic flow, passenger flow, rental cost data, and public transportation convenience, making the final location selection may not be the most cost-effective option. In addition, the location selection process that relies on manual inspections and experience judgments is time-consuming and costly, and it is difficult to cover all potential location points for comparison and analysis, which affects the efficiency of decision-making and the optimization of outlet layout.

[0003] With regard to the problem that the accuracy of network site selection in related technologies is low, which affects the rationality of network layout, no effective solution has been proposed so far. Summary of the invention

[0004] The main purpose of this application is to provide a method, device and storage medium for the site selection of a financial institution branch, so as to solve the problem in the related art that the branch site selection is determined by consulting experts and conducting on-site inspections, resulting in low accuracy of branch site selection and affecting the rationality of branch layout.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for selecting a site for a financial institution outlet is provided. The method comprises: obtaining a set of pre-selected sites, wherein the set of pre-selected sites includes X pre-selected sites, and X is a positive integer greater than 1; determining a set of service points according to the set of pre-selected sites and existing financial institution outlets; determining a set of shortest routes between each pre-selected site in the set of pre-selected sites and each service point in the set of service points based on a path planning algorithm according to the set of pre-selected sites; and determining a target site location from the set of pre-selected sites based on a P-median algorithm according to the set of shortest routes.

[0006] Furthermore, determining a set of service points based on a set of pre-selected locations and existing financial institution outlets includes: calculating the distance between each pre-selected location and each existing financial institution outlet to obtain multiple distance results; determining a minimum distance value among the multiple distance results, and determining a service range of the pre-selected location based on the minimum distance value; and determining a set of service points within the service range.

[0007] Furthermore, the service point set includes P service points, where P is a positive integer greater than 1. According to the pre-selected location set and the service point set, the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set is determined based on the path planning algorithm, including: determining a node set according to the pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1; initializing the auxiliary vector array and the node record array, wherein In the method, the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used for the nodes reached by the shortest route; a target shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set is determined, wherein the target shortest route set includes X*Y target shortest routes; each target shortest route in the target shortest route set is recorded in the auxiliary vector array, and the nodes reached by each target shortest route in the target shortest route set are recorded in the node record array.

[0008] Furthermore, initializing the auxiliary vector array and the node record array includes: setting the distances of the Y route vectors in the auxiliary vector array to infinity, wherein the route vector is a route vector corresponding to the target pre-selected location and each of the Y nodes, and the target pre-selected location is a pre-selected location in the pre-selected location set; and clearing the node record array.

[0009] Furthermore, determining the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set includes: determining the target pre-selected location as the starting node; if there is a node in the node set that is directly connected to the starting node to form a first route vector, updating the distance corresponding to the first route vector to the auxiliary vector array, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array; determining the node of the shortest distance in the distance corresponding to the first route vector as the starting node, repeating the steps of if there is a node in the node set that is directly connected to the starting node to form the first route vector, updating the distance corresponding to the route vector to the auxiliary vector array, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array, until all service points are included in the node record array after detection, and obtaining the shortest route set based on the auxiliary vector array.

[0010] Furthermore, according to the shortest route set, determining the target site selection position in the pre-site selection position set based on the P-median algorithm includes: eliminating each pre-site selection position from the pre-site selection position set in turn, determining a target pre-site selection position to be eliminated based on the sum of costs after eliminating each pre-site selection position, and eliminating the target pre-site selection position to be eliminated from the pre-site selection position set to obtain an updated pre-site selection position set, wherein the sum of costs is the sum of costs from other pre-site selection positions to the service point except the eliminated pre-site selection positions from the pre-site selection position set; repeatedly eliminating the target pre-site selection positions to be eliminated from the updated pre-site selection position set, and updating the updated pre-site selection position set again until the number in the updated pre-site selection position set is equal to the number of target sites; and using the pre-site selection positions in the updated pre-site selection position set as the target site selection positions.

[0011] Furthermore, each pre-selected location is eliminated from the pre-selected location set in turn, and a target pre-selected location to be eliminated is determined based on the sum of costs after eliminating each pre-selected location, including: determining the average passenger flow of each service point in the service point set, the rental cost data of each pre-selected location, and the number of public transportation stations within a preset range of each pre-selected location, and determining the number of target locations, wherein the number of target locations is less than the number of pre-selected locations; eliminating one pre-selected location from the pre-selected location set in turn, and calculating the sum of costs based on the average passenger flow, rental cost data and the number of public transportation stations; and determining a target pre-selected location to be eliminated from the pre-selected location set based on the sum of costs.

[0012] Furthermore, based on the average passenger flow, rental cost data and the number of public transportation stations, calculating the total cost includes: determining a first weight corresponding to the rental cost data; determining a second weight corresponding to the number of public transportation stations; and calculating the total cost based on the first weight, the second weight, the average passenger flow, rental cost data and the number of public transportation stations.

[0013] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a device for selecting a site for a financial institution outlet is provided. The device comprises: an acquisition unit, used to acquire a set of pre-selected sites, wherein the set of pre-selected sites includes X pre-selected sites, and X is a positive integer greater than 1; a first determination unit, used to determine a set of service points according to the set of pre-selected sites and existing financial institution outlets; a second determination unit, used to determine a set of shortest routes between each pre-selected site in the set of pre-selected sites and each service point in the set of service points based on a path planning algorithm according to the set of pre-selected sites; and a third determination unit, used to determine a target site from the set of pre-selected sites based on a P-median algorithm according to the set of shortest routes.

[0014] Furthermore, the first determination unit includes: a distance module, used to calculate the distance between each pre-selected location and each existing financial institution branch to obtain multiple distance results; a first determination module, used to determine the minimum distance value among the multiple distance results, and determine the service range of the pre-selected location based on the minimum distance value; a second determination module, used to determine the service point set within the service range.

[0015] Furthermore, the second determination unit includes: a third determination module, used to determine a node set according to a pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1; an initialization module, used to initialize an auxiliary vector array and a node record array, wherein the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used for the nodes reached by the shortest route; a fourth determination module, used to determine a target shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set, wherein the target shortest route set includes X*Y target shortest routes; a recording module, used to record each target shortest route in the target shortest route set into the auxiliary vector array, and record the nodes reached by each target shortest route in the target shortest route set into the node record array.

[0016] Furthermore, the initialization module includes: a setting subunit, used to set the distances of Y route vectors in the auxiliary vector array to infinity, wherein the route vector is a route vector corresponding to the target pre-selected location and each of the Y nodes, and the target pre-selected location is a pre-selected location in the pre-selected location set; and a clearing subunit, used to clear the node record array.

[0017] Furthermore, the fourth determination module includes: a first determination subunit, used to determine the target pre-selected location as the starting node; a first updating subunit, used to update the distance corresponding to the first route vector into the auxiliary vector array if there is a node in the node set that is directly connected to the starting node to form a first route vector, and write the node of the shortest distance in the distance corresponding to the first route vector into the node record array; a second updating subunit, used to determine the node of the shortest distance in the distance corresponding to the first route vector as the starting node, and repeatedly perform the steps of updating the distance corresponding to the route vector into the auxiliary vector array and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array if there is a node in the node set that is directly connected to the starting node to form the first route vector, until all service points are detected in the node record array, and the shortest route set is obtained based on the auxiliary vector array.

[0018] Furthermore, the third determination unit includes: a first elimination module, which is used to eliminate each preselected location from the preselected location set in turn, determine a target preselected location to be eliminated based on the sum of costs after eliminating each preselected location, and eliminate the target preselected location to be eliminated from the preselected location set to obtain an updated preselected location set, wherein the sum of costs is the sum of costs from other preselected locations to the service point except the eliminated preselected location from the preselected location set; a second elimination module, which is used to repeatedly eliminate the target preselected location to be eliminated from the updated preselected location set, and update the updated preselected location set again, until the number in the updated preselected location set is equal to the number of target locations; a fifth determination module, which is used to use the preselected location in the updated preselected location set as the target location.

[0019] Furthermore, the first elimination module includes: a second determination subunit, used to determine the average passenger flow of each service point in the service point set, the rental cost data of each pre-selected location, and the number of public transportation stations within a preset range of each pre-selected location, to determine the number of target locations, wherein the number of target locations is less than the number of pre-selected locations; an elimination subunit, used to eliminate one pre-selected location from the pre-selected location set in turn, and calculate the total cost based on the average passenger flow, rental cost data and the number of public transportation stations; a third determination subunit, used to determine a target pre-selected location to be eliminated from the pre-selected location set based on the total cost.

[0020] Furthermore, the elimination sub-unit includes: a first determination sub-module, used to determine a first weight corresponding to the rental cost data; a second determination sub-module, used to determine a second weight corresponding to the number of public transportation stations; and a calculation sub-module, used to calculate the total cost based on the first weight, the second weight, the average passenger flow, the rental cost data and the number of public transportation stations.

[0021] According to another aspect of the present application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any method for selecting a site for a financial institution branch.

[0022] According to another aspect of the present application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for executing a site selection method for a branch of any financial institution.

[0023] According to another aspect of the present application, a computer program product is provided, comprising computer instructions, which, when executed by a processor, implement the steps of any one of the above-mentioned methods for selecting a location for a financial institution branch.

[0024] In the embodiment of the present application, by obtaining a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, and X is a positive integer greater than 1; determining a set of service points based on the set of pre-selected locations and existing financial institution outlets; determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points based on a path planning algorithm based on the set of pre-selected locations and the set of service points; determining a target location from the set of pre-selected locations based on a P-median algorithm based on the shortest route set, the technical problem of low accuracy of location selection of outlets and the rationality of the layout of outlets is solved. In the present application, a set of pre-selected locations is obtained, a set of service points is determined in combination with existing financial institution outlets, a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points is determined based on a path planning algorithm, and finally a target location is determined from the set of pre-selected locations using a P-median algorithm, thereby achieving the technical effect of improving the accuracy of location selection of outlets and the rationality of the layout of outlets. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0026] Figure 1 A hardware structure block diagram of a computer terminal for implementing a method for selecting a location for a financial institution's outlets is shown;

[0027] Figure 2 is a flow chart of a method for selecting a location for a financial institution outlet according to an embodiment of the present application;

[0028] Figure 3 is a flow chart of determining a target shortest route set between each pre-selected location in a pre-selected location set and each service point in a service point set according to an embodiment of the present application;

[0029] Figure 4 is a schematic diagram of a site selection device for a financial institution outlet provided according to an embodiment of the present application;

[0030] Figure 5 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. For example, an interface is set up between this system and the relevant user or organization. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0034] Example 1

[0035] According to an embodiment of the present application, a method embodiment for site selection of a financial institution branch is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal (or mobile device) for implementing the location selection method of a financial institution outlet is shown. Figure 1As shown, the computer terminal 10 (or mobile device) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0037] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0038] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the site selection method of financial institution outlets in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the site selection method of the financial institution outlets mentioned above. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0039] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0040] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0041] Under the above operating environment, this application provides Figure 2 The location selection method for financial institution branches is shown. Figure 2 It is a flow chart of the site selection method for a financial institution branch according to Example 1 of the present application.

[0042] Step S201: obtaining a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, and X is a positive integer greater than 1.

[0043] For example, a financial institution plans to open a new branch in a city. Through preliminary market analysis and urban planning data, the financial institution determines a set of pre-selected locations, including X1, X2, X3, X4 and X5, a total of 5 pre-selected locations. These pre-selected locations can be the main commercial areas, residential areas or office areas of the city, etc., and they have all passed the preliminary screening and have the potential to open financial institution outlets.

[0044] Step S202, determining a service point set according to a pre-selected location set and existing financial institution outlets.

[0045] Optionally, based on the pre-selected location set X1 to X5, a service point set can be further determined. The service point is a potential high-demand area, which can be a large shopping mall P1, a densely populated residential area P2, an industrial park P3, etc. Financial institutions can determine the main service objects of the pre-selected location, that is, the service point set, by analyzing the Euclidean distance between the pre-selected location and the existing outlets, as well as the traffic data.

[0046] Step S203, according to the pre-selected location set and the service point set, determine the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set based on a path planning algorithm.

[0047] Optionally, after determining the set of pre-selected locations and the set of service points, a path planning algorithm such as the Dijkstra algorithm or the A* algorithm can be used to calculate the shortest route from each pre-selected location to each service point in the set of all service points. For example, the shortest path from X1 to P1, P2, and P3, and the shortest path from X2 to X5 to each service point are calculated. By accurately calculating the shortest route from the pre-selected location to the service point, the transportation cost and accessibility can be quantified.

[0048] Step S204, determining the target site location from the pre-site location set based on the shortest route set and the P-median algorithm.

[0049] Optionally, the P-median algorithm can be used to determine the target site location based on the shortest route set. The P-median algorithm can comprehensively consider factors such as the shortest distance from the pre-selected site location to the service point, rental cost data, passenger flow and traffic convenience. The P-median algorithm can help select the target pre-selected site location that can cover a certain number of service points with the lowest total cost among multiple pre-selected sites.

[0050] In summary, the site selection method for financial institution outlets provided in the embodiment of the present application, by obtaining a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, and X is a positive integer greater than 1; determining a set of service points according to the set of pre-selected locations and existing financial institution outlets; determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points based on a path planning algorithm according to the set of pre-selected locations and the set of service points; determining a target site selection location from the set of pre-selected locations based on a P-median algorithm according to the set of shortest routes, solves the technical problem that the accuracy of the site selection of outlets is low and affects the rationality of the layout of outlets. In the present application, a set of pre-selected locations is obtained, a set of service points is determined in combination with existing financial institution outlets, a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points is determined based on a path planning algorithm, and finally a target site selection location is determined from the set of pre-selected locations using a P-median algorithm, thereby achieving the technical effect of improving the accuracy of the site selection of outlets and the rationality of the layout of outlets.

[0051] In an optional embodiment, determining a service point set according to a pre-selected location set and existing financial institution outlets includes:

[0052] The first step is to calculate the distance between each pre-selected location and each existing financial institution branch to obtain multiple distance results.

[0053] For example, there are 5 pre-selected locations X1, X2, X3, X4 and X5, and 3 existing points N1, N2 and N3. The coordinates of the pre-selected locations are (x, y), and the coordinates of the existing points are (x0, y0). Calculate the Euclidean distance F between the existing points and the pre-selected locations. The Euclidean distances from the pre-selected location X1 to N1, N2, and N3 are calculated to be 3 km, 2.5 km, and 1.2 km, respectively. Similarly, this calculation is repeated for X2 to X5 to obtain multiple distance results.

[0054] The second step is to determine the minimum distance value among multiple distance results, and determine the service range of the pre-selected location based on the minimum distance value.

[0055] For example, in the previous step, the distance from each pre-selected location to the existing network point is obtained. For example, 1.2 kilometers from X1 to N3 is the minimum distance value, and it can be determined that the service range of the pre-selected location is an area with a radius of 1.2 kilometers.

[0056] The third step is to determine the set of service points within the service scope.

[0057] For example, within a radius of 1.2 kilometers from the pre-selected location, densely populated areas such as supermarkets, enterprises, and communities are selected as target service points.

[0058] In summary, by determining the service points at the pre-selected value locations in combination with the existing outlets, unnecessary internal competition can be avoided, the overall efficiency of the service network is improved, and the distribution of outlets of financial institutions is made more reasonable.

[0059] In an optional embodiment, if Figure 3 As shown, the service point set includes P service points, where P is a positive integer greater than 1. According to the pre-selected location set and the service point set, the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set is determined based on the path planning algorithm, including:

[0060] Step S301, determining a node set according to a pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1.

[0061] Optionally, the pre-selected locations, existing financial institutions, and surrounding intersections can be converted into nodes to form a node set. By converting geographic locations into nodes, algorithms in graph theory (such as the Dijkstra algorithm) can be used to calculate the shortest path. This not only simplifies the complexity of geographic space, but also provides mathematical tools for calculating the optimal path, thereby providing an accurate data basis for subsequent site selection decisions.

[0062] For example, there are 5 pre-selected locations (e.g., X1 to X5), 3 existing financial institution outlets (e.g., P1 to P3), and 10 intersections (e.g., N1 to N10). Then, the node set will contain Y=18 nodes, including P=3 service points and N=10 intersections, as well as 5 pre-selected locations, for a total of Y=5+3+10=18 nodes.

[0063] Step S302, initializing the auxiliary vector array and the node record array, wherein the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used to record the nodes reached by the shortest route.

[0064] Optionally, two arrays can be initialized before the path planning algorithm is performed: the auxiliary vector array is used to record the shortest route distance from the pre-selected location to each node in the node set, and the node record array is used to record the node sequence that constitutes this shortest route. Initializing these two arrays is a prerequisite for the algorithm to run, ensuring that the algorithm can start running from the correct state. In subsequent steps, the auxiliary vector array and the node record array will be continuously updated with the iteration of the algorithm, and ultimately provide the shortest path information from all pre-selected locations to all nodes, providing key data for the calculation of the P-median model.

[0065] For example, for the 5 pre-selected locations and 18 nodes in the above example, the auxiliary vector array is a 5-row 18-column matrix, with an initial value of infinity, indicating that no path has been found. The node record array is also a 5-row 18-column matrix, with an initial value of empty, used to record the shortest route to each node.

[0066] Step S303, determining a target shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set, wherein the target shortest route set includes X*Y target shortest routes.

[0067] Optionally, for the pre-selected location X1, the shortest paths to all 18 nodes in the node set (including P1 to P3 and N1 to N10) will be calculated to obtain 18 shortest routes. Similarly, for X2 to X5, the shortest paths to all 18 nodes will be obtained, totaling XY=518=90 target shortest routes.

[0068] Step S304, recording each target shortest route in the target shortest route set into the auxiliary vector array, and recording the node reached by each target shortest route in the target shortest route set into the node record array.

[0069] For example, the shortest route from the pre-selected location X1 to the service point P1 is X1->N5->P1, with a distance of 1.2km. Then, 1.2km will be recorded in the element corresponding to P1 in the auxiliary vector array, and the node sequence (N5, P1) will be recorded in the element corresponding to P1 in the node record array P.

[0070] In summary, through the above steps S301-S304, from determining the node set, initializing the array, to calculating and recording the shortest route, these steps together constitute a data-driven site selection decision framework, which not only improves the scientificity and accuracy of branch site selection, but also provides financial institutions with decision-making tools based on actual geographic information, which helps to optimize branch layout, improve service efficiency, and ultimately enhance the market competitiveness of financial institutions.

[0071] In an optional embodiment, initializing the auxiliary vector array and the node record array includes:

[0072] In the first step, the distances of the Y route vectors in the auxiliary vector array are set to infinity, wherein the route vector is a route vector corresponding to the target pre-selected location and each of the Y nodes, and the target pre-selected location is a pre-selected location in the pre-selected location set.

[0073] Optionally, the auxiliary vector array is used to store the shortest path length from the target pre-selected location to each node in the graph (including service points, intersections, etc.). When initializing the auxiliary vector array, the path lengths from all target pre-selected locations to each node are set to infinity, indicating that at the current stage of the algorithm, the shortest path length from the target pre-selected location to any node is unknown or has not yet been calculated. This is a common initialization strategy in path planning algorithms, such as Dijkstra's algorithm, because the goal of the algorithm is to gradually explore and update the shortest path information from this preset "unknown" state. Setting infinity as the initial value ensures that during the execution of the algorithm, any actual calculated path length will be recorded, because any actual path length will be less than infinity, prompting the algorithm to update the shortest path.

[0074] The second step is to clear the node record array.

[0075] Optionally, the node record array is used to store the node sequence on the shortest path to each node. In the initialization phase, since no shortest path has been found at this time, the node record array will be cleared, which means that the values ​​of all elements are undefined, or can be initialized to a special value (such as null), indicating that the shortest path from the target pre-selected location to any node has not yet been found.

[0076] In summary, the above steps can provide the necessary starting point for the operation of the path planning algorithm, and also ensure that the algorithm can effectively find and record the shortest path information from each pre-selected location to all nodes, providing basic data for the subsequent P-median location selection model calculation, so as to make more accurate network site selection decisions.

[0077] In an optional embodiment, determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points includes:

[0078] In the first step, the target pre-selected location is determined as the starting node.

[0079] Optionally, determining the target pre-selected location as the starting node can determine from which pre-selected location to start calculating the shortest path to all service points in the service point set.

[0080] In the second step, if there is a node in the node set that is directly connected to the start node to form the first route vector, the distance corresponding to the first route vector is updated to the auxiliary vector array, and the node of the shortest distance in the distance corresponding to the first route vector is written into the node record array.

[0081] For example, X1 is determined as the starting node, and the nodes directly connected to X1 are N1, N2, and P1, and the distance from X1 to N1 is 0.3km, the distance to N2 is 0.5km, and the distance to P1 is 0.8km. At this time, the auxiliary vector array D will update the distance from X1 to N1, N2, and P1 to 0.3km, 0.5km, and 0.8km respectively, and the node record array P will record the paths (X1, N1), (X1, N2), and (X1, P1).

[0082] The third step is to determine the node with the shortest distance in the distance corresponding to the first route vector as the starting node, and repeat the steps of updating the distance corresponding to the route vector into the auxiliary vector array if there is a node in the node set that is directly connected to the starting node to form the first route vector, and writing the node with the shortest distance in the distance corresponding to the first route vector into the node record array, until all service points are detected in the node record array, and the shortest route set is obtained based on the auxiliary vector array.

[0083] Optionally, the third step is the core iteration process of the algorithm, starting from the node with the shortest distance found in the second step (i.e., the node with the shortest distance in the first route vector), the exploration process of the second step is performed again until the auxiliary vector array and the node record array contain the shortest path information from the pre-selected location to all service points. This process ensures that the algorithm can gradually discover and update all possible shortest paths.

[0084] For example, the distance from X1 to N1 is the shortest, and N1 is used as the new starting node. The algorithm will start from N1 and explore the nodes directly connected to N1, such as N3, N4, and P2. Assume that the distance from N1 to N3 is 0.2km, the distance to N4 is 0.4km, and the distance to P2 is 0.6km. Then, the auxiliary vector array will update the distance from N1 to N3 to 0.5km (0.3km+0.2km), the distance to N4 to 0.7km (0.3km+0.4km), and the distance to P2 to 0.9km (0.3km+0.6km), and record the node sequences (X1, N1, N3), (X1, N1, N4), and (X1, N1, P2). This process will be repeated until all service points (P1 and P2) are marked as having found the shortest path.

[0085] In summary, through the above steps, the shortest path from the pre-selected location to the service point is found. Financial institutions can more accurately evaluate the service coverage of the selected location, provide strong data support for branch site selection, avoid inaccuracies based on intuition or experience, and improve the scientificity and accuracy of site selection decisions.

[0086] In an optional embodiment, determining the target site location in the pre-site location set based on the shortest route set and the P-median algorithm includes:

[0087] In the first step, each pre-selected location is eliminated from the pre-selected location set in turn, a target pre-selected location to be eliminated is determined based on the sum of the costs after eliminating each pre-selected location, and the target pre-selected location to be eliminated is eliminated from the pre-selected location set to obtain an updated pre-selected location set, wherein the sum of the costs is the sum of the costs from the pre-selected location set excluding the eliminated pre-selected location to the service point.

[0088] Optionally, this step is the core part of the P-median algorithm, which is to iteratively eliminate the pre-selected locations, calculate the total cost after each elimination, and then select the pre-selected location with the smallest total cost for actual elimination. This process aims to gradually determine the best subset of the pre-selected location set to form a target location set, in which the pre-selected locations will be able to minimize the total cost from the network point to the service point.

[0089] For example, the pre-selected location set includes three locations, X1, X2, and X3, and the service point set includes two service points, P1 and P2. First, calculate the total cost after removing X1, that is, the sum of the costs from X2 and X3 to P1 and P2. Assume that the total cost after removing X1 is 20, then calculate the total cost of removing X2, assuming it is 18. Finally, calculate the total cost of removing X3, assuming it is 22. In this round of iterations, the removal of X2 has the smallest total cost, so X2 is determined as the target pre-selected location to be removed and removed from the pre-selected location set to obtain the updated pre-selected location set {X1, X3}.

[0090] The second step is to repeatedly remove the target pre-selected location from the updated pre-selected location set and update the updated pre-selected location set again until the number of pre-selected locations in the updated pre-selected location set is equal to the number of target locations.

[0091] Optionally, after obtaining the first updated set of pre-selected locations, the first step will be repeated, that is, the pre-selected locations are continuously eliminated and the total cost after elimination is calculated until the number of pre-selected locations remaining in the pre-selected location set is equal to the set number of target location locations. This process ensures that the final output set of pre-selected locations can minimize the sum of the costs from the service point to the location.

[0092] For example, in the previous step, the updated pre-selected location set {X1, X3} is obtained. Assuming that the number of target locations is 1, calculate the total cost after removing X1 and X3 again. Assuming that the total cost after removing X1 is 12, and the total cost after removing X3 is 15. Therefore, X1 will be determined as the pre-selected location to be removed and removed from the set, and the final target location set {X3} is obtained.

[0093] The third step is to use the pre-selected location in the updated pre-selected location set as the target location.

[0094] Optionally, after the above iteration steps, when the preset number of pre-selected location sets is met, the remaining pre-selected location set is the target location set recommended by the algorithm. The pre-selected locations in this set will be used by financial institutions as the locations for the construction of new outlets.

[0095] For example, after the iteration of the previous step, the final pre-selected site location set {X3} is obtained, which is the target site location set recommended by the algorithm based on the P-median model.

[0096] In summary, through the optimization calculation of the P-median model, the final site selection can achieve a balance between minimizing costs and maximizing service efficiency, thereby improving the economic benefits of the network layout.

[0097] In an optional embodiment, removing each pre-selected location from the pre-selected location set in turn, and determining a target pre-selected location to be removed based on the sum of costs after removing each pre-selected location includes:

[0098] The first step is to determine the average passenger flow of each service point in the service point set, the rental cost data of each pre-selected location, the number of public transportation stations within the preset range of each pre-selected location, and the number of target locations, where the number of target locations is less than the number of pre-selected locations.

[0099] Optionally, in the preliminary stage of optimizing the site selection decision, multiple key factors affecting the site selection can be collected and analyzed, such as the average passenger flow of each service point, the rental cost data of each pre-selected location, and the convenience of public transportation near the pre-selected location. The average passenger flow reflects the potential customer demand of the service point; the rental cost data is a key factor in determining the economic feasibility of the pre-selected location; and the number of public transportation stations reflects the accessibility and convenience of the area. In addition, the number of target sites needs to be clarified, which is usually based on the expansion plan or resource allocation strategy of the financial institution.

[0100] For example, there are three pre-selected locations (X1, X2, X3) and two service points (P1, P2). The average passenger flow of service points P1 and P2 is 1000 and 1500 people / day respectively; the rental cost data of pre-selected locations X1, X2, and X3 are 2000, 1500, and 1800 yuan / month respectively; within the preset range, the number of public transportation stations near X1, X2, and X3 is 3, 2, and 4 respectively. The goal of the financial institution is to finally determine the two pre-selected locations as the target location.

[0101] In the second step, each pre-selected location is removed from the pre-selected location set one by one, and the total cost is calculated based on the average passenger flow, rental cost data and the number of public transportation stations.

[0102] For example, starting from X1, X2, and X3, remove X1 and calculate the sum of the costs from the remaining pre-selected locations (X2, X3) to P1 and P2. Due to the removal of X1, the costs from P1 to X2 and X3 increase respectively, and the cost of P2 also increases. The sum of the costs after removing X1 is calculated to be C1. Similarly, calculate the sum of the costs C2 and C3 after removing X2 and X3.

[0103] The third step is to determine a target pre-selected location to be eliminated from the pre-selected location set based on the sum of the costs.

[0104] For example, C1, C2, and C3 are 3000, 2800, and 2900, respectively. Based on the sum of costs, X1 is determined as the target pre-selected location to be eliminated because it has the highest sum of costs after elimination. By eliminating X1, the updated pre-selected location set {X2, X3} is obtained, and the second and third steps are repeated until only the target number of pre-selected locations remain in the set.

[0105] In summary, by gradually eliminating the pre-selected locations with the largest cost contribution through the above steps, the pre-selected location set can be gradually optimized to ensure that the locations in the final set can provide the minimum total cost from service point to outlet. This provides decision support based on cost optimization for financial institutions, helping them to layout new outlets more scientifically, reduce operating costs, and improve market service efficiency and customer satisfaction.

[0106] In an optional embodiment, based on average passenger flow, rental cost data and the number of public transportation stations, calculating the total cost includes:

[0107] The first step is to determine the first weight corresponding to the rental cost data.

[0108] Optionally, when determining the comprehensive cost of the pre-selected location, the rental cost data is an important indicator because it directly affects the operating cost of the financial institution's outlets. In order to reflect the importance of the rental cost data in the comprehensive cost, a weight can be set. The higher the first weight, the greater the impact of the rental cost data on the final comprehensive cost. When setting this weight, factors such as the financial strategy and cost control objectives of the financial institution can be considered.

[0109] The second step is to determine the second weight corresponding to the number of public transportation stations.

[0110] Optionally, the number of public transportation stations is another important factor, which affects the accessibility and convenience of financial institutions' outlets, and thus affects customer experience and business volume. Similar to the rental cost data, it is necessary to determine the weight of the number of public transportation stations in the comprehensive cost. The second weight reflects the degree of influence of accessibility and convenience on the location decision, which can be set based on the market strategy of the financial institution, customer preferences, etc.

[0111] The third step is to calculate the total cost based on the first weight, the second weight, the average passenger flow, the rental cost data and the number of public transportation stations.

[0112] Optionally, the cost synthesis can be calculated by the formula Among them, a is the favorable factor of convenient public transportation for the branch (that is, the second weight), b is the branch's acceptance of rental cost data (that is, the first weight), G i is the number of public transportation stations, Z iis the rental cost data, and the average flow of people is R j , D ij The shortest path from each pre-selected location to all service points.

[0113] In summary, by setting weights for rental cost data and the number of public transportation stations, and calculating the total comprehensive cost of the pre-selected locations based on these weights, a multi-factor comprehensive evaluation based on cost, transportation, and market demand can be achieved, thereby making more scientific, flexible, and market-oriented site selection decisions.

[0114] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0115] Example 2

[0116] The embodiment of the present application also provides a site selection device for a financial institution outlet. It should be noted that the site selection device for a financial institution outlet of the embodiment of the present application can be used to execute the site selection method for a financial institution outlet provided by the embodiment of the present application. The site selection device for a financial institution outlet provided by the embodiment of the present application is introduced below.

[0117] According to an embodiment of the present application, a device for implementing the above-mentioned method for selecting a location for a financial institution outlet is also provided. Figure 4 As shown, the device includes: an acquisition unit 401, a first determination unit 402, a second determination unit 403 and a third determination unit 404.

[0118] Specifically, the acquisition unit 401 acquires a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, where X is a positive integer greater than 1;

[0119] The first determining unit 402 determines a service point set according to the pre-selected location set and existing financial institution outlets;

[0120] The second determining unit 403 determines the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set based on the path planning algorithm according to the pre-selected location set and the service point set;

[0121] The third determining unit 404 determines the target site location from the pre-site location set based on the shortest route set and the P-median algorithm.

[0122] The site selection device for financial institution outlets provided in the embodiment of the present application determines a service point set according to a pre-selected location set and existing financial institution outlets through a first determination unit 402; a second determination unit 403 determines a shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set based on a path planning algorithm according to the pre-selected location set and the service point set; a third determination unit 404 determines a target site selection location from the pre-selected location set based on a P-median algorithm according to the shortest route set, thereby solving the problem of low accuracy in site selection of outlets in the related art, which affects the rationality of the outlet layout, and thereby achieving the effect of improving the accuracy of site selection of outlets and the rationality of the outlet layout.

[0123] Optionally, in the site selection device for a financial institution outlet provided in an embodiment of the present application, the first determination unit 402 includes: a distance module, used to calculate the distance between each pre-selected location and each existing financial institution outlet to obtain multiple distance results; a first determination module, used to determine the minimum distance value among the multiple distance results, and determine the service range of the pre-selected location based on the minimum distance value; and a second determination module, used to determine a set of service points within the service range.

[0124] Optionally, in the site selection device for financial institution outlets provided in the embodiment of the present application, the second determination unit 403 includes: a third determination module, used to determine a node set according to a pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1; an initialization module, used to initialize an auxiliary vector array and a node record array, wherein the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used for the nodes reached by the shortest route; a fourth determination module, used to determine a target shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set, wherein the target shortest route set includes X*Y target shortest routes; a recording module, used to record each target shortest route in the target shortest route set into the auxiliary vector array, and record the nodes reached by each target shortest route in the target shortest route set into the node record array.

[0125] Optionally, in the site selection device for a financial institution branch provided in an embodiment of the present application, the initialization module includes: a setting subunit, used to set the distances of Y route vectors in the auxiliary vector array to infinity, wherein the route vector is a route vector corresponding to a target pre-site selection position and each of the Y nodes, and the target pre-site selection position is a pre-site selection position in a set of pre-site selection positions; and a clearing subunit, used to clear the node record array.

[0126] Optionally, in the site selection device for financial institution outlets provided in the embodiment of the present application, the fourth determination module includes: a first determination subunit, used to determine the target pre-selected location as the starting node; a first updating subunit, used to update the distance corresponding to the first route vector into the auxiliary vector array if there is a node in the node set that is directly connected to the starting node to form a first route vector, and write the node of the shortest distance in the distance corresponding to the first route vector into the node record array; a second updating subunit, used to determine the node of the shortest distance in the distance corresponding to the first route vector as the starting node, and repeatedly execute the steps of updating the distance corresponding to the route vector into the auxiliary vector array if there is a node in the node set that is directly connected to the starting node to form the first route vector, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array, until all service points are included in the node record array after detection, and obtaining the shortest route set based on the auxiliary vector array.

[0127] Optionally, in the site selection device for financial institution outlets provided in the embodiment of the present application, the third determination unit 404 includes: a first elimination module, which is used to eliminate each pre-selected location from the pre-selected location set in turn, determine a target pre-selected location to be eliminated based on the sum of costs after eliminating each pre-selected location, and eliminate the target pre-selected location to be eliminated from the pre-selected location set to obtain an updated pre-selected location set, wherein the sum of costs is the sum of costs from other pre-selected locations to the service point except the eliminated pre-selected location from the pre-selected location set; a second elimination module, which is used to repeatedly execute the steps of eliminating the target pre-selected location to be eliminated from the updated pre-selected location set and updating the updated pre-selected location set again until the number in the updated pre-selected location set is equal to the number of target locations; and a fifth determination module, which is used to use the pre-selected location in the updated pre-selected location set as the target location.

[0128] Optionally, in the site selection device for financial institution outlets provided in the embodiment of the present application, the first elimination module includes: a second determination subunit, used to determine the average passenger flow of each service point in the service point set, the rental cost data of each pre-selected location, and the number of public transportation stations within a preset range of each pre-selected location, and determine the number of target site selections, wherein the number of target site selections is less than the number of pre-selected locations; an elimination subunit, used to eliminate one pre-selected location from the pre-selected location set in turn, and calculate the total cost based on the average passenger flow, rental cost data and the number of public transportation stations; and a third determination subunit, used to determine a target pre-selected location to be eliminated from the pre-selected location set based on the total cost.

[0129] Optionally, in the site selection device for financial institution outlets provided in the embodiment of the present application, the elimination sub-unit includes: a first determination sub-module, used to determine a first weight corresponding to rental cost data; a second determination sub-module, used to determine a second weight corresponding to the number of public transportation stops; and a calculation sub-module, used to calculate the total cost based on the first weight, the second weight, the average passenger flow, the rental cost data and the number of public transportation stops.

[0130] It should be noted that the acquisition unit 401, the first determination unit 402, the second determination unit 403 and the third determination unit 404 correspond to steps S201 to S204 in Example 1, and the examples and application scenarios implemented by the above four units and the corresponding steps are the same, but are not limited to the contents disclosed in the above Example 1. It should be noted that the above modules or units can be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n), and the above modules can also be run in the computer terminal 10 provided in Example 1 as part of the device.

[0131] Example 3

[0132] The embodiment of the present application may provide a computer terminal, which may be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced by a terminal device such as a mobile terminal or an electronic device.

[0133] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0134] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the site selection method of a financial institution outlet: obtaining a set of pre-selected locations, wherein the pre-selected location set includes X pre-selected locations, and X is a positive integer greater than 1; determining a set of service points based on the set of pre-selected locations and existing financial institution outlets; determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points based on a path planning algorithm based on the set of pre-selected locations and the set of service points; and determining a target site selection location from the set of pre-selected locations based on the P-median algorithm based on the shortest route set.

[0135] Optionally, the computer terminal may execute the program code of the following steps in the site selection method for a financial institution outlet: determining a set of service points based on a set of pre-selected locations and existing financial institution outlets, including: calculating the distance between each pre-selected location and each existing financial institution outlet to obtain a plurality of distance results; determining a minimum distance value among the plurality of distance results, and determining a service range of the pre-selected location based on the minimum distance value; and determining a set of service points within the service range.

[0136] Optionally, the computer terminal can execute the following program codes in the method for selecting a location for a financial institution outlet: the service point set includes P service points, P is a positive integer greater than 1, and according to the pre-selected location set and the service point set, the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set is determined based on the path planning algorithm, including: determining a node set according to the pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1; the auxiliary vector The auxiliary vector array and the node record array are initialized, wherein the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used for the nodes reached by the shortest route; a target shortest route set is determined for each pre-selected location in the pre-selected location set and each service point in the service point set, wherein the target shortest route set includes X*Y target shortest routes; each target shortest route in the target shortest route set is recorded in the auxiliary vector array, and the nodes reached by each target shortest route in the target shortest route set are recorded in the node record array.

[0137] Optionally, the computer terminal may execute the following program codes of the method for selecting a financial institution's outlets: initializing the auxiliary vector array and the node record array includes: setting the distances of the Y route vectors in the auxiliary vector array to infinity, wherein the route vector is a route vector corresponding to the target pre-selected location and each of the Y nodes, and the target pre-selected location is a pre-selected location in the set of pre-selected locations; and clearing the node record array.

[0138] Optionally, the computer terminal may execute the program code of the following steps in the site selection method for financial institution outlets: determining the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set includes: determining the target pre-selected location as the starting node; if there is a node in the node set that is directly connected to the starting node to form a first route vector, updating the distance corresponding to the first route vector to the auxiliary vector array, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array; determining the node of the shortest distance in the distance corresponding to the first route vector as the starting node, and repeatedly executing the steps of if there is a node in the node set that is directly connected to the starting node to form a first route vector, updating the distance corresponding to the route vector to the auxiliary vector array, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array, until all service points are included in the node record array after detection, and obtaining the shortest route set based on the auxiliary vector array.

[0139] Optionally, the computer terminal can execute the program code of the following steps in the site selection method for financial institution outlets: according to the shortest route set, the target site selection location is determined in the pre-site selection location set based on the P-median algorithm, including: eliminating each pre-site selection location from the pre-site selection location set in turn, determining a target pre-site selection location to be eliminated based on the sum of the costs after eliminating each pre-site selection location, and eliminating the target pre-site selection location to be eliminated from the pre-site selection location set to obtain an updated pre-site selection location set, wherein the sum of the costs is the sum of the costs from other pre-site selection locations to the service point except the eliminated pre-site selection locations from the pre-site selection location set; repeatedly eliminating the target pre-site selection locations to be eliminated from the updated pre-site selection location set, and updating the updated pre-site selection location set again, until the number of locations in the updated pre-site selection location set is equal to the number of target sites; and using the pre-site selection locations in the updated pre-site selection location set as the target site selection location.

[0140] Optionally, the computer terminal may execute the program code of the following steps in the site selection method for a financial institution outlet: eliminating each pre-selected site location from the set of pre-selected sites in turn, and determining a target pre-selected site location to be eliminated based on the sum of costs after eliminating each pre-selected site location, including: determining the average passenger flow of each service point in the service point set, the rental cost data of each pre-selected site location, and the number of public transportation stations within a preset range to which each pre-selected site location belongs, and determining the number of target sites, wherein the number of target sites is less than the number of pre-selected sites; eliminating one pre-selected site location from the set of pre-selected sites in turn, and calculating the sum of costs based on the average passenger flow, rental cost data and the number of public transportation stations; and determining a target pre-selected site location to be eliminated from the set of pre-selected sites based on the sum of costs.

[0141] Optionally, the above-mentioned computer terminal can execute the program code of the following steps in the site selection method for financial institution outlets: calculating the total cost based on the average passenger flow, rental cost data and the number of public transportation stations includes: determining the first weight corresponding to the rental cost data; determining the second weight corresponding to the number of public transportation stations; calculating the total cost based on the first weight, the second weight, the average passenger flow, rental cost data and the number of public transportation stations.

[0142] Optionally, Figure 5 is a structural block diagram of an electronic device according to an embodiment of the present application. Figure 5 As shown, the electronic device may include: one or more ( Figure 5 (only one is shown) processor 502, memory 504, storage controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0143] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the site selection method and device of the financial institution outlets in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the site selection method of the financial institution outlets mentioned above. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] The processor can call the information and application programs stored in the memory through the transmission device to execute the above steps in the site selection method for the above financial institution outlets.

[0145] By adopting the embodiment of the present application, a solution for the site selection of financial institution outlets is provided. By obtaining a set of pre-selected locations, wherein the pre-selected location set includes X pre-selected locations, and X is a positive integer greater than 1; determining a set of service points according to the set of pre-selected locations and existing financial institution outlets; determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points based on a path planning algorithm according to the set of pre-selected locations and the set of service points; determining a target site selection location from the set of pre-selected locations based on a P-median algorithm according to the shortest route set, thereby solving the technical problem that the accuracy of the site selection of outlets is low and the rationality of the layout of outlets is affected. In the present application, a set of pre-selected locations is obtained, a set of service points is determined in combination with existing financial institution outlets, a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points is determined based on a path planning algorithm, and finally a target site selection location is determined from the set of pre-selected locations using a P-median algorithm, thereby achieving the technical effect of improving the accuracy of the site selection of outlets and the rationality of the layout of outlets.

[0146] It can be understood by those skilled in the art that Figure 5 The structure shown is for illustration only, and the electronic device may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, or other terminal devices. Figure 5 The structure of the electronic device is not limited. Figure 5 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 5 Different configurations shown.

[0147] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0148] Example 4

[0149] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the location selection method for a financial institution outlet provided in the first embodiment.

[0150] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0151] Optionally, in this embodiment, the storage medium is configured to store program code for executing the following steps: obtaining a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, and X is a positive integer greater than 1; determining a set of service points based on the set of pre-selected locations and existing financial institution outlets; determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points based on a path planning algorithm based on the set of pre-selected locations and the set of service points; and determining a target location from the set of pre-selected locations based on the P-median algorithm based on the shortest route set.

[0152] Optionally, the storage medium is also configured to store program code for executing the following steps: determining a set of service points based on a set of pre-selected locations and existing financial institution outlets, including: calculating the distance between each pre-selected location and each existing financial institution outlet to obtain multiple distance results; determining a minimum distance value among the multiple distance results, and determining a service range of the pre-selected location based on the minimum distance value; and determining a set of service points within the service range.

[0153] Optionally, the storage medium is further configured to store a program code for executing the following steps: the service point set includes P service points, P is a positive integer greater than 1, and according to the pre-selected location set and the service point set, the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set is determined based on the path planning algorithm, including: determining a node set according to the pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1; the auxiliary vector array and the node array are combined. The point record array is initialized, wherein the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used for the nodes reached by the shortest route; a target shortest route set is determined for each pre-selected location in the pre-selected location set and each service point in the service point set, wherein the target shortest route set includes X*Y target shortest routes; each target shortest route in the target shortest route set is recorded in the auxiliary vector array, and the nodes reached by each target shortest route in the target shortest route set are recorded in the node record array.

[0154] Optionally, the storage medium is also configured to store program code for executing the following steps: initializing the auxiliary vector array and the node record array includes: setting the distances of the Y route vectors in the auxiliary vector array to infinity, wherein the route vector is a route vector corresponding to the target pre-selected location and each of the Y nodes, and the target pre-selected location is a pre-selected location in the pre-selected location set; clearing the node record array.

[0155] Optionally, the storage medium is also configured to store program code for executing the following steps: determining the shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set includes: determining the target pre-selected location as the starting node; if there is a node in the node set that is directly connected to the starting node to form a first route vector, updating the distance corresponding to the first route vector to the auxiliary vector array, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array; determining the node of the shortest distance in the distance corresponding to the first route vector as the starting node, repeating the steps of if there is a node in the node set that is directly connected to the starting node to form a first route vector, updating the distance corresponding to the route vector to the auxiliary vector array, and writing the node of the shortest distance in the distance corresponding to the first route vector into the node record array, until all service points are included in the node record array after detection, and obtaining the shortest route set based on the auxiliary vector array.

[0156] Optionally, the storage medium is also configured to store program code for executing the following steps: determining the target site selection location in the pre-selected site location set based on the shortest route set and the P-median algorithm, including: eliminating each pre-selected site location from the pre-selected site location set in turn, determining a target pre-selected site location to be eliminated based on the sum of costs after eliminating each pre-selected site location, and eliminating the target pre-selected site location to be eliminated from the pre-selected site location set to obtain an updated pre-selected site location set, wherein the sum of costs is the sum of costs from other pre-selected site locations to the service point excluding the eliminated pre-selected site locations from the pre-selected site location set; repeatedly eliminating the target pre-selected site location to be eliminated from the updated pre-selected site location set and updating the updated pre-selected site location set again until the number in the updated pre-selected site location set is equal to the number of target sites; and using the pre-selected site locations in the updated pre-selected site location set as the target site selection location.

[0157] Optionally, the storage medium is also configured to store program code for executing the following steps: eliminating each preselected location from the set of preselected locations in turn, and determining a target preselected location to be eliminated based on the sum of costs after eliminating each preselected location, including: determining the average passenger flow of each service point in the service point set, the rental cost data of each preselected location, and the number of public transportation stations within a preset range to which each preselected location belongs, and determining the number of target locations, wherein the number of target locations is less than the number of preselected locations; eliminating one preselected location from the set of preselected locations in turn, and calculating the sum of costs based on the average passenger flow, rental cost data and the number of public transportation stations; and determining a target preselected location to be eliminated from the set of preselected locations based on the sum of costs.

[0158] Optionally, the storage medium is also configured to store program code for performing the following steps: calculating the total cost based on the average passenger flow, rental cost data and the number of public transportation stops, including: determining a first weight corresponding to the rental cost data; determining a second weight corresponding to the number of public transportation stops; calculating the total cost based on the first weight, the second weight, the average passenger flow, rental cost data and the number of public transportation stops.

[0159] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the program steps of the site selection method for a financial institution branch.

[0160] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0161] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0162] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0163] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0165] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0166] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for selecting a location for a financial institution outlet, characterized in that: include: Acquire a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, where X is a positive integer greater than 1; Determine a set of service points based on the set of pre-selected locations and existing financial institution outlets; According to the set of pre-selected locations and the set of service points, determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points based on a path planning algorithm; According to the shortest route set, a target site selection location is determined from the pre-site selection location set based on a P-median algorithm.

2. The method according to claim 1, characterized in that Determining a service point set according to the pre-selected location set and existing financial institution outlets includes: Calculate the distance between each pre-selected location and each existing financial institution branch to obtain multiple distance results; Determine a minimum distance value among the multiple distance results, and determine a service range of the pre-selected location according to the minimum distance value; The service point set is determined within the service range.

3. The method according to claim 2, characterized in that The service point set includes P service points, where P is a positive integer greater than 1. According to the pre-selected location set and the service point set, a shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set is determined based on a path planning algorithm, including: Determine a node set according to the pre-selected location set and existing financial institution outlets, wherein the node set includes Y nodes, the Y nodes include the P service points and N intersections, Y is a positive integer greater than 2, and N is a positive integer greater than or equal to 1; Initialize an auxiliary vector array and a node record array, wherein the auxiliary vector array is used to record the shortest route from each pre-selected location in the pre-selected location set to each node in the node set, and the node record array is used for the nodes reached by the shortest route; Determine a target shortest route set between each pre-selected location in the pre-selected location set and each service point in the service point set, wherein the target shortest route set includes X*Y target shortest routes; Each target shortest route in the target shortest route set is recorded in the auxiliary vector array, and the node reached by each target shortest route in the target shortest route set is recorded in the node record array.

4. The method according to claim 3, characterized in that Initializing the auxiliary vector array and node record array includes: The distances of Y route vectors in the auxiliary vector array are set to infinity, wherein the route vector is a route vector corresponding to the target pre-selected location and each of the Y nodes, and the target pre-selected location is a pre-selected location in the pre-selected location set; Clear the node record array.

5. The method according to claim 4, characterized in that Determining a set of shortest routes between each pre-selected location in the set of pre-selected locations and each service point in the set of service points includes: Determine the target pre-selected location as a starting node; If there is a node in the node set that is directly connected to the start node to form a first route vector, the distance corresponding to the first route vector is updated to the auxiliary vector array, and the node of the shortest distance in the distance corresponding to the first route vector is written into the node record array; The node with the shortest distance in the distance corresponding to the first route vector is determined as the starting node, and the steps of updating the distance corresponding to the route vector into the auxiliary vector array and writing the node with the shortest distance in the distance corresponding to the first route vector into the node record array are repeatedly performed if there is a node in the node set that is directly connected to the starting node to form the first route vector, until all service points are detected in the node record array, and the shortest route set is obtained according to the auxiliary vector array.

6. The method according to claim 5, characterized in that According to the shortest route set, determining the target site location in the pre-site location set based on the P-median algorithm includes: Eliminate each pre-selected location from the pre-selected location set in turn, determine a target pre-selected location to be eliminated based on the sum of costs after eliminating each pre-selected location, and eliminate the target pre-selected location to be eliminated from the pre-selected location set to obtain an updated pre-selected location set, wherein the sum of costs is the sum of costs from other pre-selected locations in the pre-selected location set excluding the eliminated pre-selected location to the service point; Repeating the steps of removing the target pre-selected location to be removed from the updated pre-selected location set and updating the updated pre-selected location set again until the number of locations in the updated pre-selected location set is equal to the number of target locations; The pre-selected location in the updated pre-selected location set is used as the target location.

7. The method according to claim 6, characterized in that Eliminating each pre-selected location from the pre-selected location set in sequence, and determining a target pre-selected location to be eliminated based on the sum of costs after eliminating each pre-selected location comprises: Determine the average passenger flow of each service point in the set of service points, the rental cost data of each pre-selected location, the number of public transportation stations within a preset range of each pre-selected location, and determine the number of target locations, wherein the number of target locations is less than the number of pre-selected locations; Eliminate one pre-selected location from the pre-selected location set in turn, and calculate the total cost based on the average passenger flow, the rental cost data, and the number of public transportation stations; Based on the sum of the costs, a target pre-selected location to be eliminated is determined from the pre-selected location set.

8. The method according to claim 7, characterized in that Calculating the sum of costs based on the average passenger flow, the rental cost data and the number of public transportation stations includes: Determining a first weight corresponding to the rental cost data; Determine a second weight corresponding to the number of public transportation sites; The total cost is calculated based on the first weight, the second weight, the average passenger flow, the rental cost data and the number of public transportation stations.

9. A site selection device for a financial institution outlet, characterized in that: include: An acquisition unit, configured to acquire a set of pre-selected locations, wherein the set of pre-selected locations includes X pre-selected locations, where X is a positive integer greater than 1; A first determining unit, configured to determine a service point set according to the pre-selected location set and existing financial institution outlets; A second determining unit, configured to determine, based on the pre-selected location set and the service point set, a set of shortest routes between each pre-selected location in the pre-selected location set and each service point in the service point set based on a path planning algorithm; The third determining unit is used to determine the target site selection location from the pre-site selection location set based on the shortest route set and the P-median algorithm.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is run, the device where the computer-readable storage medium is located is controlled to execute the location selection method for a financial institution branch as described in any one of claims 1 to 8.

11. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein the program, when running, executes the method for selecting a location for a financial institution branch as described in any one of claims 1 to 8.

12. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by the processor, the steps of the method for selecting a location for a financial institution branch described in any one of claims 1 to 8 are implemented.

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