An intelligent scheduling system for logistics supply chain based on data analysis

Abstract

The present invention discloses a logistics supply chain intelligent scheduling system based on data analysis, including: a product supply information acquisition module acquires the first information of an order to be scheduled; a scheduling warehouse determination module acquires the first inventory information of the required product in each warehouse; if the difference between the first inventory information and the demand information of the order to be scheduled is greater than a first threshold, the corresponding warehouse is used as an alternative warehouse; the distance value between the delivery address information and each alternative warehouse is obtained in an electronic map, and the alternative warehouse with the smallest distance value is used as the first scheduling warehouse; if there is an idle vehicle in the first scheduling warehouse, the first scheduling warehouse is determined as the target scheduling warehouse; otherwise, the target scheduling warehouse is determined according to the schedulable value between the alternative warehouse and the first scheduling warehouse; the scheduling vehicle determination module determines the target scheduling vehicle according to the target scheduling warehouse. Thus, while the scheduling distance is the shortest, the scheduling efficiency of the scarce products in the product supply chain and the resource utilization rate of the scheduling vehicles are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics scheduling, and in particular to a logistics supply chain intelligent scheduling system based on data analysis. Background Art

[0002] With the rapid development of the telecommunications industry and the widespread deployment of 5G networks, the demand for telecommunications equipment products has increased dramatically. In order to ensure the continuity and quality of network services, the timely delivery and efficient logistics operations of telecommunications equipment products have become crucial. Although the current logistics network and technology are quite mature, there are still many challenges in the scheduling and distribution of telecommunications equipment products.

[0003] At present, when facing product shortages, many demand sides of telecommunications equipment mainly rely on emergency coordination with various warehouses and supply chains to meet order needs. Supply chain scheduling of telecommunications equipment products mostly relies on manual operations, usually by contacting various warehouse supply chains to distribute orders. Existing product supply chain scheduling usually relies on manual work, and staff contact warehouses and product supply chain shortage ends by phone to find the most suitable warehouse for the product supply chain shortage end. However, manual completion will not only cause huge waste of labor efficiency, but may also cause waste of storage resources, resulting in low scheduling efficiency. Therefore, how to improve the scientific scheduling of product supply chains has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present application provides a logistics supply chain intelligent scheduling system based on data analysis to improve the scheduling efficiency of scarce products in the product supply chain and the resource utilization rate of scheduling vehicles and warehousing.

[0005] The present application provides a logistics supply chain intelligent scheduling system based on data analysis, including a product supply information acquisition module, a scheduling warehouse determination module, and a scheduling vehicle determination module; the scheduling warehouse determination module is used to determine a target scheduling warehouse according to first information of a to-be-scheduled order acquired by the product supply information acquisition module;

[0006] The dispatch vehicle determination module is used to: determine the target dispatch vehicle according to the target dispatch warehouse; C4, take the target dispatch vehicle determined according to the target dispatch warehouse as the first dispatch vehicle, obtain the required storage space of the order to be dispatched and the available storage space of the first dispatch vehicle; C5, when the required storage space is less than or equal to the available storage space, determine the first dispatch vehicle as the target dispatch vehicle of the order to be dispatched; otherwise, obtain the sub-dispatching order of the order to be dispatched that overflows the first dispatch vehicle and its corresponding storage space as the difference storage space, determine the second dispatch vehicle of the order to be dispatched according to the difference storage space and the target dispatch warehouse, and determine the target dispatch vehicles as the first dispatch vehicle and the second dispatch vehicle;

[0007] The dispatch vehicle determination module is also used for: S201, analyzing the overlap of the delivery driving routes of the to-be-dispatched orders and the obtained first to-be-dispatched orders; S202, determining all the first to-be-dispatched orders with an overlap higher than a third threshold as a first to-be-dispatched order set; S203, in the first to-be-dispatched order set, determining at least one second to-be-dispatched order that meets the preset conditions according to the required storage space size of each first to-be-dispatched order and the second storage space size of the second dispatch vehicle, each second to-be-dispatched order includes at least one first to-be-dispatched order, and the second storage space is the remaining available storage space of the second dispatch vehicle after the difference storage space is removed;

[0008] When the second order to be scheduled determined according to the first set of orders to be scheduled is not unique, the delivery mileage optimization difference and loss coefficient factor corresponding to each first order to be scheduled in each set of second orders to be scheduled are obtained to obtain a combined evaluation value of each second order to be scheduled; the second order to be scheduled with the smallest combined evaluation value among all the second orders to be scheduled is taken as the unique second order to be scheduled that is finally determined; wherein, the method for obtaining the loss coefficient factor corresponding to the first order to be scheduled is set as: the delivery mileage optimization difference corresponding to the first order to be scheduled is input into the pre-trained carpooling loss factor prediction model corresponding to the second dispatch vehicle, and the loss coefficient factor corresponding to the first order to be scheduled is output;

[0009] S204: Allocate the second order to be dispatched to the second dispatch vehicle and establish a binding state.

[0010] Preferably, the first information of the order to be dispatched includes product demand information, shortage level, delivery address information, and required storage space, and the demand information includes the type and quantity of the product;

[0011] The system also includes a warehouse management system, which is used to count the inventory information of products and monitor the vehicle status information of the warehouse, and the vehicle status information includes two states: idle and working;

[0012] The step of determining the target scheduling warehouse according to the first information of the order to be scheduled acquired by the product supply information acquisition module includes:

[0013] Obtaining inventory information of the product in the demand information in each warehouse through the warehouse management system of each warehouse, and determining it as the first inventory information;

[0014] If the difference between the first inventory information and the demand information in the first information of the order to be scheduled is greater than a first threshold, the corresponding warehouse is used as a candidate warehouse;

[0015] Obtaining the location information of all candidate warehouses, obtaining the distance values ​​between the delivery address information and the location information of each candidate warehouse in a preset electronic map, and taking the candidate warehouse with the smallest distance value as the first dispatch warehouse;

[0016] Monitor whether there are idle vehicles in the first scheduling warehouse. If so, determine the first scheduling warehouse as the target scheduling warehouse; if not, determine the target scheduling warehouse according to the dispatchable value between the alternative warehouse and the first scheduling warehouse;

[0017] The first order to be scheduled in S201 is obtained by the product supply information acquisition module: at least one order to be scheduled is collected within a preset time window to form a first list of orders to be scheduled; the required storage space of all orders to be scheduled in the first list of orders to be scheduled is obtained respectively, and all orders to be scheduled whose required storage space is smaller than the second storage space are determined as the first order to be scheduled and transmitted to the dispatch vehicle determination module.

[0018] Preferably, in S203, obtaining the delivery mileage optimization difference and loss coefficient factor corresponding to each first order to be scheduled in each second order to be scheduled, and obtaining the combined evaluation value of each second order to be scheduled, specifically includes:

[0019] E1. Obtain all second orders to be dispatched that meet preset conditions; the preset conditions are: the sum of the storage spaces required to meet n first orders to be dispatched is less than the second storage space size of the second dispatched vehicle, and the difference between the second storage space size and the sum of the required storage space is within the space threshold range;

[0020] E2. Determine the loading rate of the second dispatch vehicle according to the set space threshold interval;

[0021] E3. For each second dispatch vehicle corresponding to the second order to be dispatched, respectively obtain the total delivery mileage D of the delivery route of the second dispatch vehicle;

[0022] The delivery mileage optimization difference Δw is obtained according to the following formula: Δw=(Pw*x*D-Sw), Pw is the cargo ratio of the wth first order to be dispatched in the second order to be dispatched in the second dispatched vehicle, x is the loading rate of the second dispatched vehicle, and D is the total delivery mileage of the delivery route of the second dispatched vehicle; the cargo ratio Pw of the wth first order to be dispatched in the second order to be dispatched in the second dispatched vehicle is calculated according to the following formula: Pw=f / F, f is the required storage space size of the wth first order to be dispatched in the second order to be dispatched, and F is the available storage space size of the second dispatched vehicle;

[0023] The combined evaluation value of each second order to be scheduled is calculated according to the following formula:

[0024]

[0025] Among them, α is the combined evaluation value of the second order to be scheduled, Δw is the optimized difference in delivery mileage corresponding to the wth first order to be scheduled in the second order to be scheduled, and Sw is the total delivery mileage of the delivery route between the target dispatching warehouse and the delivery address of the wth first order to be scheduled in the second order to be scheduled in the electronic map. is the loss coefficient factor corresponding to the wth first order to be scheduled.

[0026] Preferably, the step of determining the target scheduling warehouse according to the schedulable value between the candidate warehouse and the first scheduling warehouse includes:

[0027] Obtaining an actual dispatch route between the first dispatch warehouse and the delivery address of the order to be dispatched from a preset electronic map;

[0028] Connect the first dispatch warehouse and the location of the order to be dispatched in a straight line to obtain a virtual dispatch route;

[0029] Taking the first dispatch warehouse as the center of the circle, determining the radius according to the actual dispatch route and the virtual dispatch route, and drawing the dispatch area;

[0030] Determine an alternative warehouse that belongs to the dispatching area and has idle vehicles as the second dispatching warehouse;

[0031] According to the driving distance, driving time and driving cost between the second scheduling warehouse and the first scheduling warehouse, the dispatchable value between the second scheduling warehouse and the first scheduling warehouse is obtained respectively;

[0032] If there is a second scheduling warehouse whose corresponding schedulable value is greater than the second threshold, the first scheduling warehouse is used as the target scheduling warehouse; otherwise, the second scheduling warehouse with the smallest actual driving distance to the location of the order to be scheduled is selected as the target scheduling warehouse.

[0033] Preferably, the dispatch vehicle determination module is used to determine the target dispatch vehicle according to the target dispatch warehouse, including:

[0034] Determine whether there is an idle vehicle in the target dispatch warehouse. If so, use the idle vehicle in the target dispatch warehouse as the target dispatch vehicle;

[0035] Otherwise, the second scheduling warehouse whose scheduling value is greater than the preset threshold is used as the third scheduling warehouse;

[0036] The actual driving distances between the third dispatching warehouse and the target dispatching warehouse are respectively obtained in the electronic map, and the idle vehicle in the third dispatching warehouse with the smallest actual driving distance is used as the target dispatching vehicle.

[0037] Preferably, in C5, determining the second dispatch vehicle for the order to be dispatched according to the difference storage space and the target dispatch warehouse specifically includes:

[0038] C6. In the third dispatching warehouse, the third dispatching warehouse corresponding to the idle vehicle whose available storage space is greater than the difference storage space is used as the fourth dispatching warehouse;

[0039] C7. Use the idle vehicle of the fourth dispatching warehouse with the shortest actual driving distance to the target dispatching warehouse as the second dispatching vehicle for the order to be dispatched;

[0040] The second dispatching vehicle is bound to the sub-dispatching order of the order to be dispatched and the second order to be dispatched, and the number of orders bound to the second dispatching vehicle is W, W=w+1.

[0041] Preferably, the analyzing the overlap between the delivery routes of the order to be dispatched and the first order to be dispatched includes:

[0042] S301, obtaining the delivery routes of two orders to be dispatched, where the delivery routes consist of a series of geographic coordinate points;

[0043] S302, segmenting each delivery driving route according to certain key nodes to obtain a plurality of segments, and numbering each segment corresponding to each delivery driving route according to the driving order;

[0044] S303, respectively comparing the geographic coordinate points contained in two segments with the same label, and if the difference between the geographic coordinate points is within the error range, the two segments are determined to be overlapped;

[0045] S304: If two segments numbered 1 are detected and determined to be overlapping, the degree of overlap is calculated according to the following formula: n=n1 / N*100%, where n is the degree of overlap of the two delivery routes, n1 is the number of segments detected consecutively starting from the segment numbered 1 and determined to be overlapping, and N is the maximum number of segments of the two delivery routes.

[0046] Preferably, the logistics supply chain intelligent scheduling system further includes a delivery driving route planning module, which is used to determine the delivery driving route of the target scheduling vehicle according to the target scheduling warehouse and the target scheduling vehicle matched with the order to be scheduled, and obtain the total delivery mileage of the delivery driving route according to the electronic map, including:

[0047] D1. When the target dispatch vehicle of the order to be dispatched is the first dispatch vehicle, the driving route from the target dispatch warehouse to the delivery address of the order to be dispatched determined according to the electronic map is determined as the delivery driving route of the target dispatch vehicle;

[0048] D2. When the target dispatching vehicles of the order to be dispatched include the first dispatching vehicle and the second dispatching vehicle, the delivery driving route of the first dispatching vehicle is the same as step D1; the delivery driving route of the second dispatching vehicle is determined as:

[0049] a1. When the number of orders to be dispatched bound to the second dispatch vehicle is 1, the delivery route of the second dispatch vehicle is the same as that of the first dispatch vehicle;

[0050] a2. When the number of to-be-scheduled orders bound to the second dispatched vehicle is greater than 1, that is, the second dispatched vehicle is bound to the sub-dispatching order of the to-be-scheduled order and the second to-be-scheduled order, including:

[0051] If the delivery driving route of the first dispatched vehicle and the delivery driving route corresponding to the second order to be dispatched overlap 100%, the longest delivery driving route is determined as the delivery driving route of the second dispatched vehicle;

[0052] Otherwise, the delivery driving route of the second dispatch vehicle is replanned according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched, so as to obtain a new delivery driving route.

[0053] Preferably, the replanning of the delivery driving route of the second dispatch vehicle according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched to obtain a new delivery driving route includes:

[0054] Based on the sub-scheduled order and the second to-be-scheduled order of the to-be-scheduled order bound to the second dispatched vehicle, the one with the highest degree of shortage between the two is taken as the first order;

[0055] Mark the delivery address information of the order to be dispatched bound to the second dispatch vehicle as a target point in the electronic map, set the target dispatch warehouse as the starting point, and record the target point corresponding to the first order as the first target point;

[0056] A distance matrix is ​​constructed by taking the distance between the target dispatch warehouse and each target point, and the distance between each target point as elements;

[0057] Input the distance matrix into the preset TSP solver to obtain the shortest delivery route from the target dispatch warehouse to all target points;

[0058] Among them, the preset TSP solver is set with constraints, which are: ensuring that the first target point is the next access point after the target scheduling warehouse to meet its distribution priority.

[0059] Preferably, after S304, the method further includes:

[0060] S305, if the overlap is not equal to 100%, using the electronic map to obtain the actual driving distance between the delivery addresses of the two orders to be dispatched;

[0061] S306, obtaining the numbers corresponding to the segments detected successively and determined to be overlapped starting from the segment with the number 1, taking the end point corresponding to the segment with the largest number as the bifurcation point, and calculating the bifurcation angle value resulting from the bifurcation of the two delivery driving routes at the bifurcation point;

[0062] S307, calculating the adjusted overlap according to the following formula: P=n*(1-e1*s)*(1-e2*θ), wherein P is the adjusted overlap, n is the overlap before adjustment, s is the actual driving distance between the delivery addresses of the two orders to be scheduled, normalized according to the preset distance threshold interval, θ is the bifurcation angle normalized according to the preset angle threshold interval, e1 is the weight value corresponding to the actual driving distance between the delivery addresses of the two orders to be scheduled, and e2 is the weight value corresponding to the bifurcation angle;

[0063] S308, replacing the original overlap value with the adjusted overlap degree.

[0064] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0065] The dispatch warehouse module determines the first dispatch warehouse based on inventory information and distance information, and introduces the dispatchable value between the first dispatch warehouse and the second dispatch warehouse, that is, time efficiency and benefit, when there is no idle vehicle in the first dispatch warehouse, to evaluate whether the calling efficiency between the second dispatch warehouse and the first dispatch warehouse is within an acceptable range. Further judgment on the target dispatch warehouse avoids the subsequent dispatch vehicle calling time being too long due to the lack of idle vehicles in the warehouse, thereby reducing the distribution efficiency, improving the distribution efficiency and resource utilization, and minimizing the mileage of the distribution route of the target dispatch vehicle, thereby improving the distribution efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a structural diagram of a logistics supply chain intelligent scheduling system based on data analysis according to an embodiment of the present invention;

[0067] Figure 2 A schematic diagram of the working process of the dispatch vehicle determination module in an embodiment of the present invention;

[0068] Figure 3 A schematic diagram of a flow chart of analyzing the overlap between the delivery routes of an order to be scheduled and a second order to be scheduled according to an embodiment of the present invention;

[0069] Figure 4The present invention is a flowchart of replanning the delivery route of the second dispatching vehicle according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched, respectively. DETAILED DESCRIPTION

[0070] To facilitate the understanding of the present invention, the present application will be described more comprehensively below with reference to the relevant drawings; the drawings show preferred embodiments of the present invention, but the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, the purpose of providing these embodiments is to enable a more thorough and comprehensive understanding of the disclosed content of the present invention.

[0071] It should be noted that the terms “vertical”, “horizontal”, “up”, “down”, “left”, “right” and similar expressions used in this document are only for illustrative purposes and do not represent the only implementation method.

[0072] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs; the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more related listed items.

[0073] Example 1: In the logistics supply chain of telecommunications equipment products, ensuring the timeliness and accuracy of product delivery is crucial to maintaining the stable operation of the communication network. Telecom operators, as the demand side of equipment, have strict requirements on the types, quantities, and delivery times of products. In order to meet these requirements, the intelligent scheduling system needs to efficiently determine which warehouse to dispatch goods from and select appropriate vehicles for delivery. However, in actual operation, some warehouses may be close to the demand side, but there are no idle vehicles in the warehouse for scheduling, and vehicles need to be called from other places to drive to the warehouse. At this time, if the scheduling warehouse is selected based only on inventory and distance, it may lead to waste of subsequent vehicle scheduling time and reduced delivery efficiency.

[0074] Figure 1 It is a structural diagram of a logistics supply chain intelligent scheduling system based on data analysis according to an embodiment of the present invention.

[0075] like Figure 1 As shown, a logistics supply chain intelligent scheduling system based on data analysis includes: a product supply information acquisition module, a scheduling warehouse determination module, a scheduling vehicle determination module, and a warehouse management system. Each warehouse is equipped with a warehouse management system.

[0076] The product supply information acquisition module establishes a connection with the information system of the product demand side to obtain the orders to be scheduled and the first information of the orders to be scheduled and transmit it to the scheduling warehouse determination module; the first information includes the demand information, shortage level, required storage capacity, delivery time information and delivery address information of the product. Among them, the demand information of the product includes the type and quantity of the product.

[0077] The warehouse management system is used to count the inventory information of products and monitor the vehicle status information of the warehouse. The vehicle status information includes two states: idle and working. Each warehouse management system is assigned a unique identifier, which indicates the location information of the corresponding warehouse.

[0078] The scheduling warehouse determination module is used to determine the target scheduling warehouse according to the first information of the order to be scheduled, specifically including:

[0079] A1. Obtain inventory information of the product required in the first information in each warehouse through the warehouse management system of each warehouse, and determine it as the first inventory information.

[0080] A2. If the difference between the first inventory information and the demand information in the first information of the order to be scheduled is greater than a first threshold, the corresponding warehouse is used as a candidate warehouse.

[0081] The first threshold is used to ensure that the inventory of the product in the warehouse is sufficient.

[0082] A3. Obtain the location information of all candidate warehouses through the warehouse management system of each warehouse, obtain the distance value between the delivery address information and the location information of each candidate warehouse in the preset electronic map, and select the candidate warehouse with the smallest distance value as the first scheduling warehouse.

[0083] A4. Monitor whether there are idle vehicles in the first scheduling warehouse. If so, determine the first scheduling warehouse as the target scheduling warehouse; if not, determine the target scheduling warehouse based on the dispatchable value between the alternative warehouse and the first scheduling warehouse.

[0084] In some embodiments, determining the target scheduling warehouse according to the schedulable value between the candidate warehouse and the first scheduling warehouse specifically includes:

[0085] B1. Obtaining the actual dispatching route between the first dispatching warehouse and the delivery address of the order to be dispatched from a preset electronic map.

[0086] B2. Connect the first dispatch warehouse and the location of the order to be dispatched in a straight line to obtain a virtual dispatch route.

[0087] B3. Take the first dispatch warehouse as the center of the circle, determine the radius according to the actual dispatch route and the virtual dispatch route, and draw the dispatch area.

[0088] Specifically, the calculation formula for the radius is: r=(u0 / U0+v0 / V0)*L, where u0 represents the straight-line distance between the first scheduling warehouse and the midpoint of the virtual scheduling route, U0 represents the driving distance value between the first scheduling warehouse and the midpoint of the virtual scheduling line segment on the electronic map, v0 represents the straight-line distance between the location of the order to be scheduled and the midpoint of the virtual scheduling line segment, V0 represents the driving distance value between the location of the order to be scheduled and the midpoint of the virtual scheduling line segment on the electronic map, and L represents the driving distance value of the scheduling route between the first scheduling warehouse and the location of the order to be scheduled.

[0089] B4. Determine the alternative warehouse that belongs to the scheduling area and has idle vehicles as the second scheduling warehouse.

[0090] B5. According to the driving distance, driving time and driving cost between the second scheduling warehouse and the first scheduling warehouse, the dispatchable value between the second scheduling warehouse and the first scheduling warehouse is obtained respectively.

[0091] Specifically, the dispatchability value is defined as a comprehensive indicator that reflects the time efficiency and cost effectiveness of the vehicle picking up goods from the second dispatch warehouse to the first dispatch warehouse.

[0092] First, the normalized values ​​of driving distance, driving time and driving cost are obtained according to the preset evaluation system, and the dispatchable value is calculated according to the following formula: q=1 / a*b*c, where a is the normalized value of driving distance, b is the normalized value of driving time, and c is the normalized value of driving cost. The evaluation system is connected to the electronic map and the consumption cost is evaluated according to the type of vehicle. The normalized value is calculated according to the maximum and minimum values ​​set in the actual situation. For example, the driving distance from the second scheduling warehouse A to the first scheduling warehouse is 10km, the minimum distance set according to the actual situation is 5km, and the maximum distance is 20km, then a=(10-5) / (20-5)=0.33.

[0093] B6. If there is a second scheduling warehouse whose corresponding dispatchable value is greater than the second threshold, the first scheduling warehouse is used as the target scheduling warehouse; otherwise, the second scheduling warehouse with the smallest actual driving distance to the location of the order to be scheduled is selected as the target scheduling warehouse.

[0094] The dispatch vehicle determination module is used to determine the target dispatch vehicle according to the target dispatch warehouse, specifically including:

[0095] C1. Determine whether there is an idle vehicle in the target dispatch warehouse. If so, use the idle vehicle in the target dispatch warehouse as the target dispatch vehicle. Otherwise, proceed to C2.

[0096] C2. The second scheduling warehouse whose scheduling value is greater than the preset threshold is used as the third scheduling warehouse.

[0097] C3. Obtain the actual driving distances between the third dispatching warehouse and the target dispatching warehouse in the electronic map, and use the idle vehicle in the third dispatching warehouse with the smallest actual driving distance as the target dispatching vehicle.

[0098] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0099] The dispatch warehouse module determines the first dispatch warehouse based on inventory information and distance information, and introduces the dispatchable value between the first dispatch warehouse and the second dispatch warehouse, that is, time efficiency and benefit, when there is no idle vehicle in the first dispatch warehouse, to evaluate whether the calling efficiency between the second dispatch warehouse and the first dispatch warehouse is within an acceptable range. Further judgment on the target dispatch warehouse avoids the subsequent dispatch vehicle calling time being too long due to the lack of idle vehicles in the warehouse, thereby reducing the distribution efficiency, and improving the distribution efficiency and resource utilization.

[0100] Embodiment 2: In embodiment 1, the target dispatching warehouse and the target dispatching vehicle are matched for the order to be dispatched to realize the distribution scenario of one order, one warehouse and one vehicle. However, the factors between the required storage space of the order to be dispatched and the available storage space of the target dispatching vehicle are not taken into consideration. When the required storage space of the order to be dispatched is larger than the available storage space of the target dispatching vehicle, there is a target dispatching vehicle that is not compatible with the order to be dispatched, and the target dispatching vehicle needs to be reselected, thereby affecting the dispatching efficiency.

[0101] Therefore, the embodiments of the present application are optimized to a certain extent based on the above embodiments.

[0102] In some embodiments, the dispatch vehicle determination module is further used to:

[0103] C4. Using the target dispatch vehicle determined by the target dispatch warehouse as the first dispatch vehicle, and obtaining the required storage space of the order to be dispatched and the available storage space of the first dispatch vehicle;

[0104] C5. When the required storage space is less than or equal to the available storage space, the first dispatch vehicle is determined as the target dispatch vehicle for the order to be dispatched; otherwise, the sub-dispatching order of the order to be dispatched that overflows the first dispatch vehicle is obtained and the storage space corresponding to the sub-dispatching order is used as the difference storage space, and step C6 is executed;

[0105] C6. In the third dispatching warehouse, the third dispatching warehouse corresponding to the idle vehicle whose available storage space is greater than the difference storage space is used as the fourth dispatching warehouse;

[0106] C7. Use the idle vehicle of the fourth dispatching warehouse with the shortest actual driving distance to the target dispatching warehouse as the second dispatching vehicle for the order to be dispatched;

[0107] C8. Determine that the target dispatching vehicles for the order to be dispatched are the first dispatching vehicle and the second dispatching vehicle.

[0108] Furthermore, since the second dispatch vehicle corresponding to the order to be dispatched still has remaining storage space after removing the difference storage space, if the second dispatch vehicle is simply used to deliver sub-dispatching orders of the order to be dispatched, it may cause a large-scale problem of low utilization of dispatch vehicle storage space, thereby resulting in low utilization of dispatch resources.

[0109] In some embodiments, the dispatch vehicle determination module is further used to record the remaining available storage space of the second dispatch vehicle corresponding to the order to be dispatched after removing the difference storage space as the second storage space and transmit it to the product supply information acquisition module, and the product supply information acquisition module is further used to:

[0110] Collecting at least one order to be scheduled within a preset time window to form a first list of orders to be scheduled;

[0111] It should be noted that all the orders to be scheduled in the first list of orders to be scheduled are defined as other orders to be scheduled collected within the same preset time window as the orders to be scheduled in the first embodiment.

[0112] The required storage spaces of all the orders to be dispatched in the first list of orders to be dispatched are respectively obtained, and all the orders to be dispatched whose required storage spaces are smaller than the second storage space are determined as first orders to be dispatched and transmitted to the dispatch vehicle determination module.

[0113] It should be noted that the first order to be dispatched is determined as a set of orders that preliminarily meet the second storage space of the second dispatched vehicle, and is not limited to a certain quantity.

[0114] In some embodiments, Figure 2 As shown, the dispatch vehicle determination module is also used for:

[0115] S201, using a preset electronic map, respectively obtain the delivery routes between the delivery address of the first order to be dispatched and the delivery address of the order to be dispatched and the target dispatching warehouse, and analyze the overlap between the delivery routes of the order to be dispatched and the first order to be dispatched.

[0116] The delivery route is the route from the target dispatch warehouse to the delivery address of the order to be dispatched in the electronic map.

[0117] S202: Determine all first orders to be dispatched whose delivery route overlaps higher than a third threshold as a first set of orders to be dispatched.

[0118] S203, in the first set of orders to be scheduled, according to the required storage space size of each first order to be scheduled and the second storage space size of the second scheduling vehicle, determine the second orders to be scheduled, the second orders to be scheduled including w first orders to be scheduled, wherein w is a positive integer greater than 0.

[0119] Specifically, the preset condition for determining the second order to be dispatched is: the sum of the storage space required to meet the n first orders to be dispatched is less than the second storage space size of the second dispatched vehicle, and the difference between the second storage space size and the sum of the required storage space is within the space threshold interval. The space threshold interval is used to limit the size range of the remaining storage space of the second dispatched vehicle to ensure that storage space resources are not excessively wasted.

[0120] S204: Allocate the second order to be dispatched to the second dispatch vehicle and establish a binding state.

[0121] Therefore, the second dispatch vehicle is bound to the sub-dispatching order of the order to be dispatched and the second order to be dispatched, and the number of orders bound to the second dispatch vehicle is W, W=w+1.

[0122] The third threshold is set according to actual conditions and can be set to 70%.

[0123] In some embodiments, the overlap between the delivery routes of the order to be dispatched and the first order to be dispatched is analyzed, such as Figure 3 As shown, specifically including:

[0124] S301, obtaining the delivery routes of two orders to be dispatched, where the delivery routes consist of a series of geographic coordinate points;

[0125] S302, segmenting each delivery driving route according to certain key nodes to obtain a plurality of segments, and numbering each segment corresponding to each delivery driving route according to the driving order, each segment can be regarded as a small straight line segment or a curve segment, and the key node can be set as a traffic intersection or a traffic light;

[0126] S303, respectively comparing the geographic coordinate points contained in two segments with the same label, and if the difference between the geographic coordinate points is within the error range, the two segments are determined to be overlapped;

[0127] S304: If two segments numbered 1 are detected and determined to be overlapping, the degree of overlap is calculated according to the following formula: n=n1 / N*100%, where n is the degree of overlap of the two delivery routes, n1 is the number of segments detected consecutively starting from the segment numbered 1 and determined to be overlapping, and N is the maximum number of segments of the two delivery routes.

[0128] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0129] By obtaining the required storage space of the order to be dispatched and the available storage space of the target dispatch vehicle, and selecting a fourth dispatch warehouse from the third dispatch warehouse as the second dispatch vehicle when necessary, the situation that the required storage space of the order to be dispatched is greater than the available storage space of the target dispatch vehicle, which may require the target dispatch vehicle to be reselected, is avoided, thereby improving the dispatch efficiency;

[0130] The dispatch vehicle module reuses the remaining available storage space of the second dispatch vehicle corresponding to the to-be-dispatched order after removing the difference storage space. By collecting the to-be-dispatched orders within a preset time window and determining the to-be-dispatched orders whose required storage space is less than the second storage space as the second to-be-dispatched orders, the second dispatch vehicle can be fully utilized, thus avoiding the waste of storage space, improving resource utilization, and effectively solving the dispatch conflict and resource allocation problems of receiving multiple to-be-dispatched orders within the same time window;

[0131] By analyzing the overlap of the delivery routes of the order to be dispatched and the second order to be dispatched, the second order to be dispatched with an overlap higher than a third threshold is allocated to the corresponding second dispatch vehicle. This enables the delivery of multiple orders to be completed in one delivery process, reducing the number of delivery vehicles and driving distances, thereby optimizing the delivery route and reducing the delivery cost.

[0132] Embodiment 3: In embodiment 2, the first dispatch vehicle and the second dispatch vehicle are determined according to the required storage space of the order to be dispatched and a binding relationship is established. The delivery driving routes of the first dispatch vehicle and the second dispatch vehicle for the order to be dispatched are not set. Since the second dispatch vehicle may have multiple orders to be dispatched with which a binding relationship is established, the planning of the delivery driving route is extremely critical to the delivery efficiency.

[0133] In some embodiments, the logistics supply chain intelligent scheduling system also includes a delivery route planning module, which is used to determine the delivery route of the target scheduling vehicle based on the target scheduling warehouse and the target scheduling vehicle matched with the order to be scheduled, and obtain the total delivery mileage of the delivery route based on the electronic map.

[0134] Specifically, according to the target dispatch warehouse and target dispatch vehicle matched with the order to be dispatched, the delivery route of the target dispatch vehicle is determined, including:

[0135] D1. When the target dispatch vehicle of the order to be dispatched is the first dispatch vehicle, the driving route from the target dispatch warehouse to the delivery address of the order to be dispatched determined according to the electronic map is determined as the delivery driving route of the target dispatch vehicle.

[0136] D2. When the target dispatching vehicles of the order to be dispatched include the first dispatching vehicle and the second dispatching vehicle, the delivery driving route of the first dispatching vehicle refers to D1; the delivery driving route of the second dispatching vehicle is determined as:

[0137] a1. When the number of orders bound to the second dispatch vehicle is 1, the delivery route of the second dispatch vehicle is the same as that of the first dispatch vehicle;

[0138] a2. When the number of orders bound to the second dispatch vehicle is greater than 1, that is, the second dispatch vehicle is bound to the sub-dispatching order of the order to be dispatched and the second order to be dispatched, including:

[0139] If the delivery driving route of the first dispatched vehicle and the delivery driving route corresponding to the second order to be dispatched overlap 100%, the longest delivery driving route is determined as the delivery driving route of the second dispatched vehicle;

[0140] Otherwise, the delivery driving route of the second dispatch vehicle is replanned according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched, so as to obtain a new delivery driving route.

[0141] Among them, the delivery route of the second dispatch vehicle is replanned according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched, and a new delivery route is obtained, such as Figure 4 As shown, specifically including:

[0142] S401, based on the sub-scheduled order of the to-be-scheduled order bound to the second dispatched vehicle and the second to-be-scheduled order, the one with the highest degree of shortage between the two is taken as the first order.

[0143] S402, the delivery address information of the order bound to the second dispatch vehicle is marked as a target point in the electronic map, the target point corresponding to the first order is recorded as the first target point, and the target dispatch warehouse is set as the starting point.

[0144] S403, constructing a distance matrix using the distance between the target scheduling warehouse and each target point, and the distance between each target point as elements.

[0145] S404, input the distance matrix into a preset TSP solver to obtain the shortest delivery route starting from the target dispatch warehouse to visit all target points.

[0146] The TSP solver may be an exact algorithm, such as the branch and bound method, or an approximate algorithm, such as a genetic algorithm or a simulated annealing algorithm, which will not be elaborated in the present invention.

[0147] Specifically, a constraint condition is set in the preset TSP solver, and the constraint condition is: to ensure that the first target point is the next access point after the target scheduling warehouse to meet its delivery priority.

[0148] Furthermore, in Example 2, a scheduling optimization scheme based on the overlap of delivery driving routes is proposed, and the overlap is calculated to determine whether to assign the first order to be scheduled to the second dispatched vehicle of the order to be scheduled. However, in actual applications, it is found that there are limitations in simply relying on the number of segment overlaps to calculate the overlap, especially when two delivery driving routes diverge at a certain point, and the delivery addresses of the two orders to be scheduled are far apart and the route divergence angle is large, using the same vehicle for delivery may lead to reduced delivery efficiency. This is because the vehicle needs to re-plan the route according to the two delivery addresses, first arrive at one delivery address, and then go to the other delivery address. If the distance between the two delivery addresses exceeds a certain threshold, the driving distance and time will inevitably increase.

[0149] In some embodiments, in step S304, the method further includes:

[0150] S305, if the overlap is not equal to 100%, using the electronic map to obtain the actual driving distance between the delivery addresses of the two orders to be dispatched;

[0151] S306, obtaining the numbers corresponding to the segments detected successively and determined to be overlapped starting from the segment with the number 1, taking the end point corresponding to the segment with the largest number as the bifurcation point, and calculating the bifurcation angle value resulting from the bifurcation of the two delivery driving routes at the bifurcation point;

[0152] S307, calculate the adjusted overlap according to the following formula: P=n*(1-e1*s)*(1-e2*θ), where P is the adjusted overlap, n is the overlap before adjustment, s is the actual driving distance between the delivery addresses of the two orders to be scheduled, which is normalized according to the lower and upper limits of the preset distance threshold interval, θ is the bifurcation angle normalized according to the lower and upper limits of the preset angle threshold interval, e1 is the weight value corresponding to the actual driving distance between the delivery addresses of the two orders to be scheduled, and e2 is the weight value corresponding to the bifurcation angle.

[0153] It should be noted that, based on actual conditions or historical experience, a distance threshold interval and an angle threshold interval are pre-set, and the distance threshold interval and the angle threshold interval indicate the degree of safety when the target dispatching vehicle simultaneously delivers two orders to be dispatched and is affected by the actual driving distance values ​​and bifurcation angle values ​​of the delivery addresses of the two orders to be dispatched.

[0154] S308, replacing the original overlap value with the adjusted overlap degree.

[0155] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0156] By introducing the delivery route planning module, the delivery route of the target dispatch vehicle can be intelligently planned. In particular, when the target dispatch vehicle has a second dispatch vehicle and the number of orders bound to the second dispatch vehicle is greater than 1, the route can be replanned according to the delivery address information between the orders to ensure that the target dispatch vehicle completes the delivery task of all orders with the shortest distance while ensuring that the most scarce orders can be delivered in time.

[0157] By calculating and adjusting the overlap, the efficiency of using the same dispatch vehicle to deliver multiple orders can be evaluated more accurately. When the distance between two delivery addresses is far or the divergence angle is large, the system can intelligently choose whether to assign these orders to the same vehicle, thereby avoiding unnecessary increase in driving distance and time, reducing energy consumption and vehicle wear, optimizing the utilization of logistics resources, effectively reducing invalid driving and repeated routes, and significantly improving delivery efficiency.

[0158] Embodiment 4: In Embodiment 2 and Embodiment 3, the second dispatch vehicle is used for carpooling, and the second order to be dispatched and the sub-order of the order to be dispatched are determined by calculating the overlap of the delivery driving routes of the order to be dispatched and the first order to be dispatched. However, since the second order to be dispatched only needs to satisfy the requirement that the sum of the required storage space is less than the second storage space size of the second dispatch vehicle and the difference between the second storage space size and the sum of the required storage space is within the space threshold range, the determined second order to be dispatched is not unique. For example, the first set of orders to be dispatched includes four orders B, C, D, and E. Among these four orders, there are two cases for the determined second order to be dispatched: B+C and C+D+E.

[0159] In addition, in order to successfully find a group order whose delivery route overlaps with the order to be dispatched and meets the third threshold within the preset time window, the third threshold is set at 70% instead of 90% to avoid group order failure. However, this approach also has a defect. Since the overlap is not highly overlapped, although the second dispatched vehicle uses the contents of the above steps S401 to S404 to calculate the shortest driving distance, the shortest driving distance is only the shortest distance of the second dispatched vehicle passing through all delivery address points. There may be a certain order whose delivery route is too different from the carpooling delivery route, resulting in a lower delivery efficiency of the carpooling delivery for this order to a certain extent. In this case, the second dispatched vehicle is extremely critical in selecting the second order to be dispatched.

[0160] In view of the above situation, in order to ensure that the delivery route of the second dispatched vehicle is the shortest, the above content needs to be further optimized, that is, the selection of the second order to be dispatched needs to be further limited.

[0161] In some embodiments, step S203 further includes:

[0162] E1. If the second order to be scheduled determined according to the first set of orders to be scheduled is not unique, then all second orders to be scheduled that meet the preset conditions are obtained, and each second order to be scheduled is obtained according to a combination of several first orders to be scheduled in the first set of orders to be scheduled, and each combination of the second orders to be scheduled is different.

[0163] E2. Determine the loading rate x of the second dispatched vehicle according to the set space threshold interval, which can be set to 90%, indicating the ratio of the cargo space actually loaded on the vehicle to the available storage space, so as to optimize the vehicle utilization.

[0164] E3. For each second dispatch vehicle corresponding to the second order to be dispatched, the total delivery mileage D of the delivery route of the second dispatch vehicle is obtained.

[0165] E4. Calculate the combined evaluation value of each second order to be scheduled according to the following formula: α=Δ1 / S1+Δ2 / S2+...+Δw / Sw.

[0166] Among them, α is the combined evaluation value of the second order to be scheduled, Δw is the optimized delivery mileage difference corresponding to the w-th first order to be scheduled in the second order to be scheduled, and Sw is the total delivery mileage of the delivery route between the target scheduling warehouse and the delivery address of the w-th first order to be scheduled in the second order to be scheduled in the electronic map, that is, the delivery route of the w-th first order to be scheduled in the second order to be scheduled for separate delivery without carpooling.

[0167] Specifically, the optimized delivery mileage difference Δw can be obtained according to the following formula: Δw=(Pw*x*D-Sw), where Pw is the cargo ratio of the wth first order to be dispatched in the second order to be dispatched in the second dispatch vehicle, x is the loading rate of the second dispatch vehicle, and D is the total delivery mileage of the delivery route of the second dispatch vehicle.

[0168] Specifically, the cargo ratio Pw of the wth first order to be scheduled in the second order to be scheduled in the second scheduling vehicle is calculated according to the following formula: Pw=f / F, where f is the required storage space size of the wth first order to be scheduled in the second order to be scheduled, and F is the available storage space size of the second scheduling vehicle.

[0169] E5. The second order to be scheduled with the smallest combined evaluation value α among all the second orders to be scheduled is taken as the second order to be scheduled finally determined in step S204.

[0170] In some embodiments, in step E4, the calculation method of the combined evaluation value of each second order to be scheduled may also be set as:

[0171]

[0172] in, is the combined evaluation value of the second order to be scheduled, Δw is the optimized difference in delivery mileage corresponding to the wth first order to be scheduled in the second order to be scheduled, Sw is the total delivery mileage of the delivery route between the target dispatching warehouse and the delivery address of the wth first order to be scheduled in the second order to be scheduled in the electronic map, that is, the delivery route of the wth first order to be scheduled in the second order to be scheduled for separate delivery without carpooling, is the loss coefficient factor corresponding to the wth first order to be scheduled, which is used to Adaptive adjustments are made to make the calculated combination evaluation value more realistic and more accurately evaluate the beneficial effect of the carpooling combination of the second order to be scheduled on the overall delivery efficiency. The smaller the loss coefficient factor, the greater the beneficial effect.

[0173] Specifically, the method for obtaining the loss coefficient factor corresponding to the first order to be scheduled is set as: inputting the delivery mileage optimization difference Δw corresponding to the wth first order to be scheduled into the pre-trained carpooling loss factor prediction model corresponding to the second scheduling vehicle, and outputting the loss coefficient factor corresponding to the first order to be scheduled.

[0174] The pre-trained carpooling loss factor prediction model corresponding to different second dispatch vehicles is specifically obtained in the following ways:

[0175] F1. Collect all historical carpooling data of the second dispatch vehicle, including the optimized delivery mileage difference of all historical first orders to be dispatched in each historical delivery route, and the corresponding actual delivery efficiency impact value (the actual delivery efficiency impact value is an evaluation index for quantifying the delivery efficiency after the first order to be dispatched is successfully delivered, and the range is set to [0,1]. It can be obtained based on professional logistics delivery experience or the actual evaluation score of the delivery result by the delivery receiving end user. The larger the actual delivery efficiency impact value, the worse the actual efficiency of this delivery, and the present invention does not limit this);

[0176] F2. Set a label for the optimized difference in delivery mileage of each historical first order to be dispatched, and set the content of the label to its corresponding actual delivery efficiency impact value to form a training sample set;

[0177] F3. Use the training sample set to train the pre-set machine learning model and optimize the parameters to obtain the final carpooling loss factor prediction model. In the output layer of the model, the weighted summation of several actual delivery efficiency influence values ​​matched according to the input delivery mileage optimization difference can be performed to output the corresponding loss coefficient factor.

[0178] It should be noted that during the training of the model, the training sample set can also be classified according to the types of all historical first orders to be scheduled (daily necessities, food, factory supplies, etc.) to obtain the carpooling loss factor prediction model corresponding to different order types, and the optimized delivery mileage difference and the type of the first order to be scheduled are converted into feature vectors, labeled, and model training is performed to obtain the final differentiated model, thereby more accurately outputting the loss factor of the corresponding order carpooling prediction and improving the accuracy of the final order combination evaluation value.

[0179] Therefore, the delivery characteristics and historical performance of different carpooling vehicles are differentiated, and the actual delivery results corresponding to the delivery mileage optimization difference corresponding to a large number of historical carpooling orders of different dispatched vehicles are quantified. The negative impact of carpooling on delivery efficiency is quantified, and the loss coefficient factor output by the prediction model is used to adaptively adjust the changes in the carpooling mileage of the current first order to be dispatched. For different order combinations, the combined evaluation value is made more in line with reality, better reflecting the real impact of the carpooling combination on the overall delivery efficiency, thereby improving the reliability of the combined evaluation value.

[0180] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0181] By introducing the combined evaluation value α, the impact of different second orders to be dispatched on the delivery mileage can be more accurately evaluated, which helps to avoid the problem of a significant drop in the delivery efficiency of individual orders due to carpooling. When calculating the combined evaluation value α, the difference in delivery mileage of each first order to be dispatched in the two cases of carpooling and individual delivery is taken into account, which makes the evaluation more comprehensive and accurate, and can better reflect the impact of carpooling on the overall delivery efficiency.

[0182] Since multiple possible combinations of second orders to be dispatched are considered, the second order to be dispatched with the smallest combination evaluation value α is selected and bound to the second dispatch vehicle, which can effectively ensure that the overall delivery efficiency is optimized during carpooling delivery, thereby minimizing the mileage of the delivery route of the second dispatch vehicle and improving the delivery efficiency.

[0183] Embodiment 5: In order to further improve the efficiency of product supply and distribution, when the target dispatching vehicle needs to drive to the target dispatching warehouse for loading first, in order to avoid the target dispatching vehicle arriving at the target dispatching warehouse and having to wait too long because the relevant orders to be dispatched have not been picked up yet, resulting in vehicle congestion outside the warehouse park, the warehouse management system of the target dispatching warehouse is extremely critical.

[0184] Therefore, the embodiments of the present application are optimized to a certain extent based on the above embodiments.

[0185] In some embodiments, the dispatch vehicle determination module is further used to transmit the cargo preparation priority of the target dispatch vehicle, the to-be-dispatched order bound to the target dispatch vehicle, and the first information of the to-be-dispatched order to the warehouse management system corresponding to the target dispatch warehouse.

[0186] In some embodiments, the warehouse management system is also used to:

[0187] Count the pending dispatch orders and the corresponding target dispatch vehicles that are matched to the target dispatch warehouse within the preset time window;

[0188] Assign cargo preparation priority to each target dispatch vehicle based on the highest shortage of orders to be dispatched in each target dispatch vehicle.

[0189] The warehouse of the embodiment of the present invention is provided with a closed shelf, and the closed shelf is provided with a plurality of storage locations, and a corresponding product is placed in each storage location.

[0190] The warehouse management system is used to prepare the goods for the to-be-scheduled orders bound to the target dispatching vehicles in sequence using the sensing device connected to the warehouse management system according to the cargo preparation priority of each target dispatching vehicle, specifically including:

[0191] The warehouse management system is connected to a closed shelf control system, and generates cargo location information of a target dispatch vehicle according to demand information of the order to be dispatched, the cargo location information includes a closed shelf number and a storage location number, and transmits the cargo location information to the closed shelf control system;

[0192] Among them, the sensing device establishes connections with the access control system set up in the warehouse and the storage space in the warehouse through radio frequency identification technology; the closed shelf control system is used to control the status of the corresponding storage space according to the received cargo location information. The closed shelf control system records the type and quantity of products in the storage space corresponding to each closed shelf. Therefore, the warehouse management system generates the cargo location information of the target dispatching vehicle according to the closed shelf control system and the demand information of the order to be dispatched.

[0193] The staff wears a sensor device to go to the warehouse to pick up the goods. When the staff approaches the warehouse's sensor access control, the access control system reads the identity information through the sensor device and verifies their permission to pick up the goods;

[0194] After receiving the cargo location information sent by the warehouse management system, the closed shelf control system indicates the storage location through the indicator light set on the closed shelf and turns on the sensing system of the corresponding storage location;

[0195] When the staff approaches the storage location in turn according to the indicator light, the storage location system senses the sensing device and automatically opens the storage location door.

[0196] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0197] By assigning cargo preparation priorities to each target dispatch vehicle, the warehouse management system can prioritize urgent or in-demand orders, ensuring that these orders can be prepared in a timely manner and delivered quickly to their destination.

[0198] Through the cooperation of induction devices with closed shelves and access control systems, it can be ensured that only authorized staff can access and pick up goods. In addition, using radio frequency identification technology, each step of operation can be accurately recorded and tracked, thereby enhancing the traceability of goods and the accuracy of inventory management. Intelligent equipment such as indicator lights and automatically opened storage doors reduce the time and effort of staff in finding goods and manually opening storage doors, improve their work efficiency, avoid long waiting times outside the warehouse park and possible traffic congestion, and further improve overall logistics efficiency.

[0199] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A logistics supply chain intelligent scheduling system based on data analysis, characterized in that: It includes a product supply information acquisition module, a dispatch warehouse determination module, and a dispatch vehicle determination module; the dispatch warehouse determination module is used to determine the target dispatch warehouse according to the first information of the to-be-dispatched order acquired by the product supply information acquisition module; The dispatch vehicle determination module is used to: determine the target dispatch vehicle according to the target dispatch warehouse; C4. The target dispatch vehicle determined according to the target dispatch warehouse is used as the first dispatch vehicle, and the required storage space of the order to be dispatched and the available storage space of the first dispatch vehicle are obtained; C5. When the required storage space is less than or equal to the available storage space, the first dispatch vehicle is determined as the target dispatch vehicle for the order to be dispatched; Otherwise, the sub-dispatching order of the to-be-dispatched order that overflows the first dispatching vehicle and its corresponding storage space are obtained as the difference storage space, and the second dispatching vehicle of the to-be-dispatched order is determined according to the difference storage space and the target dispatching warehouse, and the target dispatching vehicles are determined to be the first dispatching vehicle and the second dispatching vehicle; The dispatch vehicle determination module is further used to: S201, analyze the overlap between the delivery driving routes of the to-be-dispatched orders and the obtained first to-be-dispatched orders; S202, determine all the first to-be-dispatched orders whose overlap is higher than a third threshold as a first to-be-dispatched order set; S203, in the first set of orders to be dispatched, according to the required storage space size of each first order to be dispatched and the second storage space size of the second dispatched vehicle, determining at least one second order to be dispatched that meets the preset conditions, each second order to be dispatched includes at least one first order to be dispatched, and the second storage space is the remaining available storage space of the second dispatched vehicle after deducting the difference storage space; The first order to be scheduled is obtained by the product supply information acquisition module: at least one order to be scheduled is collected within a preset time window to form a first list of orders to be scheduled; Respectively obtain the required storage space of all the orders to be dispatched in the first list of orders to be dispatched, determine all the orders to be dispatched whose required storage space is smaller than the second storage space as the first orders to be dispatched and transmit them to the dispatch vehicle determination module; When the second orders to be scheduled determined according to the first set of orders to be scheduled are not unique, the delivery mileage optimization difference and loss coefficient factor corresponding to each first order to be scheduled in each set of second orders to be scheduled are obtained to obtain a combined evaluation value of each set of second orders to be scheduled; The second order to be scheduled with the smallest combined evaluation value among all the second orders to be scheduled is taken as the only second order to be scheduled that is finally determined; wherein, the method for obtaining the loss coefficient factor corresponding to the first order to be scheduled is set as follows: the delivery mileage optimization difference corresponding to the first order to be scheduled is input into the pre-trained carpooling loss factor prediction model corresponding to the second dispatch vehicle, and the loss coefficient factor corresponding to the first order to be scheduled is output; S204: Allocate the second order to be dispatched to the second dispatch vehicle and establish a binding state.

2. The intelligent logistics supply chain scheduling system based on data analysis as claimed in claim 1 is characterized in that: The first information of the order to be dispatched includes product demand information, shortage level, delivery address information, and required storage space, and the demand information includes the type and quantity of the product; The system also includes a warehouse management system, which is used to count the inventory information of products and monitor the vehicle status information of the warehouse, and the vehicle status information includes two states: idle and working; The step of determining the target scheduling warehouse according to the first information of the order to be scheduled acquired by the product supply information acquisition module includes: Obtaining inventory information of the product in the demand information in each warehouse through the warehouse management system of each warehouse, and determining it as the first inventory information; If the difference between the first inventory information and the demand information in the first information of the order to be scheduled is greater than a first threshold, the corresponding warehouse is used as a candidate warehouse; Obtaining the location information of all candidate warehouses, obtaining the distance values ​​between the delivery address information and the location information of each candidate warehouse in a preset electronic map, and taking the candidate warehouse with the smallest distance value as the first dispatch warehouse; Monitor whether there are idle vehicles in the first scheduling warehouse. If so, determine the first scheduling warehouse as the target scheduling warehouse; if not, determine the target scheduling warehouse based on the dispatchable value between the alternative warehouse and the first scheduling warehouse.

3. The logistics supply chain intelligent scheduling system based on data analysis as claimed in claim 1 is characterized in that: In S203, the delivery mileage optimization difference and loss coefficient factor corresponding to each first order to be scheduled in each second order to be scheduled are obtained to obtain a combined evaluation value of each second order to be scheduled, specifically including: E1. Obtain all second orders to be dispatched that meet preset conditions; the preset conditions are: the sum of the storage spaces required to meet n first orders to be dispatched is less than the second storage space size of the second dispatched vehicle, and the difference between the second storage space size and the sum of the required storage space is within the space threshold range; E2. Determine the loading rate of the second dispatch vehicle according to the set space threshold interval; E3. For each second dispatch vehicle corresponding to the second order to be dispatched, respectively obtain the total delivery mileage D of the delivery route of the second dispatch vehicle; The delivery mileage optimization difference Δw is obtained according to the following formula: Δw=(Pw*x*D-Sw), Pw is the cargo ratio of the wth first order to be dispatched in the second order to be dispatched in the second dispatched vehicle, x is the loading rate of the second dispatched vehicle, and D is the total delivery mileage of the delivery route of the second dispatched vehicle; the cargo ratio Pw of the wth first order to be dispatched in the second order to be dispatched in the second dispatched vehicle is calculated according to the following formula: Pw=f / F, f is the required storage space size of the wth first order to be dispatched in the second order to be dispatched, and F is the available storage space size of the second dispatched vehicle; The combined evaluation value of each second order to be scheduled is calculated according to the following formula: Among them, α is the combined evaluation value of the second order to be scheduled, Δw is the optimized difference in delivery mileage corresponding to the wth first order to be scheduled in the second order to be scheduled, and Sw is the total delivery mileage of the delivery route between the target dispatching warehouse and the delivery address of the wth first order to be scheduled in the second order to be scheduled in the electronic map. is the loss coefficient factor corresponding to the wth first order to be scheduled.

4. The logistics supply chain intelligent scheduling system based on data analysis as claimed in claim 2 is characterized in that: The step of determining the target scheduling warehouse according to the schedulable value between the candidate warehouse and the first scheduling warehouse includes: Obtaining an actual dispatch route between the first dispatch warehouse and the delivery address of the order to be dispatched from a preset electronic map; Connect the first dispatch warehouse and the location of the order to be dispatched in a straight line to obtain a virtual dispatch route; Taking the first dispatch warehouse as the center of the circle, determining the radius according to the actual dispatch route and the virtual dispatch route, and drawing the dispatch area; Determine an alternative warehouse that belongs to the dispatching area and has idle vehicles as the second dispatching warehouse; According to the driving distance, driving time and driving cost between the second scheduling warehouse and the first scheduling warehouse, the dispatchable value between the second scheduling warehouse and the first scheduling warehouse is obtained respectively; If there is a second scheduling warehouse whose corresponding schedulable value is greater than the second threshold, the first scheduling warehouse is used as the target scheduling warehouse; otherwise, the second scheduling warehouse with the smallest actual driving distance to the location of the order to be scheduled is selected as the target scheduling warehouse.

5. The data analysis-based logistics supply chain intelligent scheduling system according to claim 4 is characterized in that: The dispatch vehicle determination module is used to determine the target dispatch vehicle according to the target dispatch warehouse, including: Determine whether there is an idle vehicle in the target dispatch warehouse. If so, use the idle vehicle in the target dispatch warehouse as the target dispatch vehicle; Otherwise, the second scheduling warehouse whose scheduling value is greater than the preset threshold is used as the third scheduling warehouse; The actual driving distances between the third dispatching warehouse and the target dispatching warehouse are respectively obtained in the electronic map, and the idle vehicle in the third dispatching warehouse with the smallest actual driving distance is used as the target dispatching vehicle.

6. The data analysis-based logistics supply chain intelligent scheduling system according to claim 5, characterized in that: In C5, determining the second dispatch vehicle for the order to be dispatched according to the difference storage space and the target dispatch warehouse specifically includes: C6. In the third dispatching warehouse, the third dispatching warehouse corresponding to the idle vehicle whose available storage space is greater than the difference storage space is used as the fourth dispatching warehouse; C7. Use the idle vehicle of the fourth dispatching warehouse with the shortest actual driving distance to the target dispatching warehouse as the second dispatching vehicle for the order to be dispatched; The second dispatching vehicle is bound to the sub-dispatching order of the order to be dispatched and the second order to be dispatched, and the number of orders bound to the second dispatching vehicle is W, W=w+1.

7. The logistics supply chain intelligent scheduling system based on data analysis as claimed in claim 1 is characterized in that: The analyzing the overlap between the delivery routes of the order to be dispatched and the first order to be dispatched obtained includes: S301, obtaining the delivery routes of two orders to be dispatched, where the delivery routes consist of a series of geographic coordinate points; S302, segmenting each delivery driving route according to certain key nodes to obtain a plurality of segments, and numbering each segment corresponding to each delivery driving route according to the driving order; S303, respectively comparing the geographic coordinate points contained in two segments with the same label, and if the difference between the geographic coordinate points is within the error range, the two segments are determined to be overlapped; S304: If two segments numbered 1 are detected and determined to be overlapping, the degree of overlap is calculated according to the following formula: n=n1 / N*100%, where n is the degree of overlap of the two delivery routes, n1 is the number of segments detected consecutively starting from the segment numbered 1 and determined to be overlapping, and N is the maximum number of segments of the two delivery routes.

8. The data analysis-based logistics supply chain intelligent scheduling system according to claim 6, characterized in that: The logistics supply chain intelligent scheduling system also includes a delivery route planning module, which is used to determine the delivery route of the target scheduling vehicle according to the target scheduling warehouse and the target scheduling vehicle matched with the order to be scheduled, and obtain the total delivery mileage of the delivery route according to the electronic map, including: D1. When the target dispatch vehicle of the order to be dispatched is the first dispatch vehicle, the driving route from the target dispatch warehouse to the delivery address of the order to be dispatched determined according to the electronic map is determined as the delivery driving route of the target dispatch vehicle; D2. When the target dispatching vehicles of the order to be dispatched include the first dispatching vehicle and the second dispatching vehicle, the delivery driving route of the first dispatching vehicle is the same as step D1; the delivery driving route of the second dispatching vehicle is determined as: a1. When the number of orders to be dispatched bound to the second dispatch vehicle is 1, the delivery route of the second dispatch vehicle is the same as that of the first dispatch vehicle; a2. When the number of to-be-scheduled orders bound to the second dispatched vehicle is greater than 1, that is, the second dispatched vehicle is bound to the sub-dispatching order of the to-be-scheduled order and the second to-be-scheduled order, including: If the delivery driving route of the first dispatched vehicle and the delivery driving route corresponding to the second order to be dispatched overlap 100%, the longest delivery driving route is determined as the delivery driving route of the second dispatched vehicle; Otherwise, the delivery driving route of the second dispatch vehicle is replanned according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched, so as to obtain a new delivery driving route.

9. The data analysis-based logistics supply chain intelligent scheduling system according to claim 8, characterized in that: The replanning of the delivery driving route of the second dispatch vehicle according to the delivery address information corresponding to the order to be dispatched and the second order to be dispatched to obtain a new delivery driving route includes: Based on the sub-scheduled order and the second to-be-scheduled order of the to-be-scheduled order bound to the second dispatched vehicle, the one with the highest degree of shortage between the two is taken as the first order; Mark the delivery address information of the order to be dispatched bound to the second dispatch vehicle as a target point in the electronic map, set the target dispatch warehouse as the starting point, and record the target point corresponding to the first order as the first target point; A distance matrix is ​​constructed by taking the distance between the target dispatch warehouse and each target point, and the distance between each target point as elements; Input the distance matrix into the preset TSP solver to obtain the shortest delivery route from the target dispatch warehouse to all target points; Among them, the preset TSP solver is set with constraints, which are: ensuring that the first target point is the next access point after the target scheduling warehouse to meet its distribution priority.

10. The intelligent logistics supply chain scheduling system based on data analysis according to claim 7, characterized in that: After S304, the method further includes: S305, if the overlap is not equal to 100%, using the electronic map to obtain the actual driving distance between the delivery addresses of the two orders to be dispatched; S306, obtaining the numbers corresponding to the segments detected successively and determined to be overlapped starting from the segment with the number 1, taking the end point corresponding to the segment with the largest number as the bifurcation point, and calculating the bifurcation angle value resulting from the bifurcation of the two delivery driving routes at the bifurcation point; S307, calculating the adjusted overlap according to the following formula: P=n*(1-e1*s)*(1-e2*θ), wherein P is the adjusted overlap, n is the overlap before adjustment, s is the actual driving distance between the delivery addresses of the two orders to be scheduled, normalized according to the preset distance threshold interval, θ is the bifurcation angle normalized according to the preset angle threshold interval, e1 is the weight value corresponding to the actual driving distance between the delivery addresses of the two orders to be scheduled, and e2 is the weight value corresponding to the bifurcation angle; S308, replacing the original overlap value with the adjusted overlap degree.

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