A method, device, equipment and medium for dividing a port hinterland

Abstract

The application discloses a port hinterland division method, device, equipment and medium, relates to the field of transportation network planning, and the method comprises the following steps: acquiring the cumulative transportation cost, cumulative time and time value of each section of transportation route in all feasible paths from each starting city to each port, the feasible path comprising at least one of highway, railway and river network transportation, the cumulative transportation cost comprising the total cost of conversion of transportation mode, and the cumulative time comprising the total waiting time of conversion of transportation mode; determining the minimum generalized cost from each starting city to each port based on the cumulative transportation cost, cumulative time and time value of all feasible paths; determining the target probability of selecting each port for the corresponding starting city based on the minimum generalized cost from any starting city to each port and the comprehensive attraction of each port to the corresponding starting city; and dividing the port hinterland of each port based on the target probability of selecting each port for each starting city.

Description

Technical Field

[0001] This application relates to the field of transportation network planning technology, and in particular to a method, apparatus, equipment and medium for dividing port hinterland. Background Technology

[0002] As the core area radiating the port economy, the port hinterland directly affects its cargo distribution capacity, logistics efficiency, and regional economic synergy. With the deepening of globalization, competition among ports has shifted from competition based solely on throughput to competition for hinterland resources. This is especially true within overlapping economic zones (such as port clusters in the Bohai Rim and Yangtze River Delta), where the ambiguity of hinterland boundaries has intensified, leading to resource allocation conflicts and efficiency losses. Accurate and dynamic port hinterland delineation helps to understand the resource status and economic potential within the hinterland, serving as a fundamental basis for determining the rational division of labor among ports and for port layout, planning, and operation.

[0003] However, the methods for dividing port hinterlands in related technologies cannot support accurate identification of port hinterlands under different scenarios. Summary of the Invention

[0004] The purpose of this application is to provide a method, apparatus, equipment, medium, and product for dividing the hinterland of a port.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] Firstly, this application provides a method for delineating the hinterland of a port, including:

[0007] The cumulative transportation cost, cumulative time, and time value of each segment of the transportation route are obtained from each originating city to each port. The time value is the value loss of the goods per unit time. The feasible routes include at least one of road, rail, and river network transportation. The cumulative transportation cost includes the total cost of changing modes of transportation. The cumulative time includes the total waiting time for changing modes of transportation.

[0008] Based on the cumulative transportation costs, cumulative time, and time value of all feasible routes, determine the minimum generalized cost from each of the originating cities to each of the ports;

[0009] Based on the minimum generalized cost from any of the aforementioned departure cities to each of the aforementioned ports and the comprehensive attractiveness of each of the aforementioned ports to the corresponding departure cities, determine the target probability of the corresponding departure city choosing each of the aforementioned ports.

[0010] Based on the target probability of selecting each port from each departure city, the hinterland of each port is divided.

[0011] Secondly, this application provides a device for delineating the hinterland of a port, comprising:

[0012] The first acquisition module is used to acquire the cumulative transportation cost, cumulative time, and time value of each segment of the transportation route in all feasible paths from each originating city to each port. The time value is the value loss of the goods per unit time. The feasible paths include at least one of road, rail, and river network transportation. The cumulative transportation cost includes the total cost of changing transportation modes. The cumulative time includes the total waiting time for changing transportation modes.

[0013] The first determining module is used to determine the minimum generalized cost from each of the originating cities to each of the ports based on the cumulative transportation cost, the cumulative time, and the time value of all feasible routes.

[0014] The second determining module is used to determine the target probability of a corresponding departure city choosing each of the ports based on the minimum generalized cost from any of the departure cities to each of the ports and the comprehensive attractiveness of each port to the corresponding departure city.

[0015] The partitioning module is used to partition the hinterland of each port based on the target probability of selecting each port for each departure city.

[0016] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the port hinterland division method described in any one of the above.

[0017] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the port hinterland division method described above.

[0018] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the port hinterland division method described above.

[0019] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0020] This application provides a method, apparatus, equipment, medium, and product for dividing port hinterland. By incorporating the time value of money into the cost system, it breaks through the limitations of traditional methods that only calculate transportation costs, and is closer to the actual needs of time-sensitive goods (such as fresh produce and electronic components). It supports single or combined transportation modes such as road, rail, and river networks, covering feasible routes throughout the entire "door-to-port" chain, and solves the limitations of traditional methods that only consider a single transportation mode. By including the total cost of changing transportation modes when calculating cumulative transportation costs and the total waiting time for changing transportation modes when calculating cumulative time, it performs cost accounting from multiple dimensions, increasing... The consideration of the cost of switching modes of transport during multimodal transport reflects the true losses in multimodal transport. By calculating the generalized cost (economic cost + time cost) of all feasible paths through an algorithm, the optimal path corresponding to the minimum generalized cost is automatically selected, avoiding the subjectivity and inefficiency of manual planning. By determining the target probability of the originating city choosing each port based on the minimum generalized cost from any of the originating cities to each of the ports and the comprehensive attractiveness of each port to the corresponding originating city, the port hinterland is divided according to the target probability, thereby enabling more accurate division of the port hinterland. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a method for dividing the hinterland of a port, provided as an embodiment of this application;

[0023] Figure 2 A flowchart illustrating a method for dividing the hinterland of a port, provided as another embodiment of this application;

[0024] Figure 3 A schematic diagram of traffic network data provided in an embodiment of this application;

[0025] Figure 4 A schematic diagram of a transportation route provided for an embodiment of this application;

[0026] Figure 5 A flowchart illustrating a method for dividing the hinterland of a port, as provided in another embodiment of this application;

[0027] Figure 6 A flowchart illustrating a method for dividing the hinterland of a port, as provided in another embodiment of this application;

[0028] Figure 7 A flowchart illustrating a method for dividing the hinterland of a port is provided in another embodiment of this application;

[0029] Figure 8 A flowchart illustrating a method for dividing the hinterland of a port is provided in another embodiment of this application;

[0030] Figure 9 A schematic diagram of the functional modules of a port hinterland delineation device provided in an embodiment of this application;

[0031] Figure 10 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0033] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] In one exemplary embodiment, such as Figure 1 As shown, a method for delineating the hinterland of a port is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, it includes steps 102 to 108. Wherein:

[0035] Step 102: Obtain the cumulative transportation cost, cumulative time, and time value of each segment of the transportation route from each originating city to each port. The time value is the value loss of the goods per unit time. The feasible routes include at least one of road, rail, and river network transportation. The cumulative transportation cost includes the total cost of changing transportation modes. The cumulative time includes the total waiting time for changing transportation modes.

[0036] The feasible path refers to all possible transportation routes for goods from the city of origin to the port, including at least one of the following modes of transportation: road, rail, and river network (i.e., river transport). The cumulative transportation cost is the sum of all costs incurred during the entire transportation process from the city of origin to the port, through each segment of the transportation route. The cumulative transportation cost includes the total transportation cost of different modes of transportation and the total cost of switching between different modes of transportation (i.e., the total cost of switching modes of transportation). Specifically, the total transportation cost may include fuel costs, toll fees, vehicle wear and tear costs, and driver labor costs for road transportation routes; train freight, track usage fees, and loading and unloading fees for rail transportation routes; and ship rental fees, port berthing fees, and waterway passage fees for river network transportation routes. The total cost of switching modes of transportation is the sum of the costs of multiple switching modes of transportation. The cost of switching modes of transportation may include loading and unloading fees, warehousing fees, handling fees, and equipment rental fees.

[0037] The cumulative time is the total time required for goods to travel from the city of origin to the port, including the total transportation time of different modes of transport and the total waiting time when switching between different modes of transport (i.e., the total waiting time for switching modes of transport). The total transportation time can specifically include the travel time of road transport routes, the train travel time of railway transport routes, and the ship navigation time of river network transport routes. The total waiting time for switching modes of transport is the sum of the waiting time for multiple switching of modes of transport. The waiting time for switching modes of transport can include the time for waiting for loading and unloading equipment, the time for waiting for the next means of transport, customs clearance time, etc.

[0038] The value loss of goods per unit time can refer to the amount of value reduction caused by each unit of delay (or stay) during transportation (such as 1 day or 1 hour). It is a key indicator for measuring the impact of transportation time on the value of goods. The value loss of goods per unit time varies depending on the type of goods. For example, the value loss per unit time of fresh products, seasonal goods (such as holiday gifts and fashion), and precision instruments is greater than that of bulk commodities such as coal.

[0039] Step 104: Based on the cumulative transportation cost, cumulative time, and time value of all feasible routes, determine the minimum generalized cost from each of the originating cities to each of the ports;

[0040] For example, step 104 can be replaced by the following steps 1041 to 1042:

[0041] Step 1041: Based on the cumulative transportation cost, cumulative time, and time value of all feasible paths, determine the generalized cost corresponding to each feasible path;

[0042] The generalized cost, also known as generalized transportation cost, is typically used to convert time cost into economic cost so that it can be combined with transportation costs during the transportation process to form a generalized cost that comprehensively evaluates transportation efficiency. Based on the cumulative time and the time value, the cumulative time cost can be calculated. Based on the cumulative transportation cost and the cumulative time cost, the generalized cost of each feasible path can be calculated. The cumulative transportation cost can be represented as C, the cumulative time as T, and the time value as C0. T Generalized cost can be expressed as C g Then the generalized cost of each path can be expressed by the following formula (1):

[0043] C g =C+C T ×T(1);

[0044] Step 1042: Based on the shortest path search algorithm, determine the minimum generalized cost from each of the originating cities to each of the ports.

[0045] Taking the originating city O and port D as an example, the shortest path search algorithm can be used to find the optimal path from the originating city to the port in a given transportation network. First, define a set O containing the center points of all originating cities and a set D containing all ports. Second, form a point pair (oi, dj) matrix (i.e., the generalized cost OD matrix) based on a one-to-one correspondence between sets O and D. Next, traverse all feasible paths from oi to dj and record the corresponding generalized transportation costs, selecting the minimum value as the minimum cost cost (oi, dj) from oi to dj (i.e., the minimum generalized cost). Finally, traverse all (oi, dj) point pairs until the minimum cost between all originating and destination points is determined, i.e., the minimum generalized cost from each originating city to each port is determined. The minimum generalized cost can be expressed as C. gmin Then the minimum generalized cost of each path can be expressed by the following formula (2):

[0046] C gmin =min(C g (2);

[0047] Step 106: Based on the minimum generalized cost from any of the originating cities to each of the ports and the comprehensive attractiveness of each port to the corresponding originating city, determine the target probability of the corresponding originating city choosing each of the ports.

[0048] Among them, the target probability is the probability of each city belonging to different ports. The hinterland of a port can be the geographical area of ​​the port's cargo throughput and services, that is, the economic influence area of ​​the port's origin and destination of cargo and passengers. It is the core link between the port and the inland economy, reflecting the port's radiation capacity and economic absorption range. The attraction of a port to its hinterland can be compared to gravity in physics. Gravity models can be used to describe the spatial interaction between the port and its hinterland. The Hough model and the field strength model are both port hinterland identification models built on gravity models. The key is how to accurately and effectively estimate the parameters of the model. According to the principle of gravity model, the choice of port for cargo transportation is not only related to the comprehensive attractiveness of the port, but also closely related to the minimum generalized cost between the port and the departure city. Therefore, the port selection probability model can be expressed as shown in the following formula (3):

[0049]

[0050] Among them, P o-di A represents the probability that the shipping city O will choose the i-th port as the destination; di Let C be the overall attractiveness of the i-th port to the departure city O; g,odi Let β be the minimum generalized cost from the originating city O to the i-th port. The minimum generalized cost can be calculated based on the previous content. β is the friction coefficient of the generalized cost, which is generally taken as 2.

[0051] Because changes in routes and freight rates under different scenarios may result in the sum of probabilities of a given origin city for all ports not being equal to 1, the target probability needs to be corrected to ensure that the sum of the target probability values ​​for each city for different ports is equal to 1. The corrected probability can be calculated using the following formula (4):

[0052]

[0053] Among them, P′ o-di P represents the probability that the originating city O will choose the i-th port after the correction; o-di The target probability of selecting the i-th port for the originating city O. The sum of the target probabilities of selecting all ports for the departure city O.

[0054] Step 108: Based on the target probability of selecting each port for each departure city, divide the hinterland of each port.

[0055] Based on the target probability of a port being chosen by its originating city, a port's hinterland can be divided to determine its dominant and competitive hinterlands. A dominant hinterland is a geographical area where a port holds absolute dominance (e.g., a specific originating city), where goods almost exclusively choose that port for transport, making it difficult for other ports to compete. A port's dominant hinterland typically shares geographical proximity, transportation monopoly, and industrial dependence with its corresponding port. A competitive hinterland is a geographical area contested by multiple ports (e.g., a specific originating city), where goods can choose different ports for transport, and competition among ports occurs through price, service efficiency, and shipping network. A port's competitive hinterland typically shares geographical accessibility equilibrium, cargo flow diversion, dynamic game theory, and cross-regional overlap with its corresponding ports. A single originating city can only be a dominant hinterland for one port, but it can also be a competitive hinterland for multiple ports. A port can have multiple dominant and competitive hinterlands. By comparing the port hinterland division results under different scenarios, targeted port optimization strategies can be developed.

[0056] In this embodiment, by incorporating time value into the cost system, it breaks through the limitations of traditional methods that only calculate transportation costs, and is closer to the actual needs of time-sensitive goods (such as fresh produce and electronic components); it supports single or combined transportation modes such as highways, railways, and river networks, covering feasible paths throughout the "door-to-port" chain, and solves the limitations of traditional methods that only consider a single transportation mode; by including the total cost of changing transportation modes when calculating cumulative transportation costs and the total waiting time for changing transportation modes when calculating cumulative time, it performs cost accounting from multiple dimensions, increases the consideration of the cost of changing transportation modes in multimodal transport, and reflects the real losses of multimodal transport; by calculating the generalized cost (economic cost + time cost) of all feasible paths through an algorithm, it automatically selects the optimal path corresponding to the minimum generalized cost, avoiding the subjectivity and inefficiency of manual planning; by determining the target probability of the originating city choosing each port based on the minimum generalized cost from any of the originating cities to each of the ports and the comprehensive attractiveness of each port to the corresponding originating city, it then divides the port hinterland according to the target probability, thereby enabling more accurate division of the port hinterland.

[0057] In another exemplary embodiment of this application, such as Figure 2 As shown, the method for dividing the port hinterland also includes the following steps:

[0058] Step 1011: Obtain location data for all ports and cities within the target area;

[0059] As shown in Table 1 below, the location data of all ports and all cities within the target area can be obtained respectively, and the location data can be represented by longitude and latitude.

[0060] Table 1 Example of Port Location Information

[0061] Port ID Port Name longitude latitude 1 Yichang Port 110.2874 30.7855 2 Wuhan Port 113.2217 30.2312 3 Nanjing Port 118.4423 32.0554

[0062] Table 2 Example of City Center Location Information

[0063] City ID City Name longitude latitude 1 Zhongxiang City 112.2874 31.1005 2 Zigui County 110.1812 30.3811 3 Xiantao City 112.5549 30.0432

[0064] Step 1012: Based on the location data, construct transportation network data, which includes highway data, railway data, and river network data. The highway data includes highway distance, highway time, and highway unit distance transportation cost. The railway data includes railway distance, railway time, and railway unit distance transportation cost. The river network data includes river network distance, river network time, and river network unit distance transportation cost.

[0065] The transportation network data mentioned above can also be called transportation route data, including all highway data, railway data, river network data, etc. First, as shown in Table 3 below, railway data, highway data, and river network data can be processed separately to form interconnected transportation network data. Information such as length (i.e., distance), speed, time, and unit distance transportation cost are added to the edges in the network. It should be noted that the unit of length is kilometers (KM), the unit of speed is kilometers per hour (KM / h), the unit of time is hours (h), and the unit of unit distance transportation cost is yuan.

[0066] Table 3 Examples of boundary key information in transportation network data

[0067] Side ID starting node Termination Node length speed time Unit distance transportation cost 1 1 2 60 60 1 10 2 3 4 120 60 2 20 3 5 6 90 60 1.5 15

[0068] Step 1013: Identify nodes in the traffic network data that can switch modes of transportation, and add waiting time and the cost of switching modes of transportation to each node; determine the total cost of switching modes of transportation based on the cost of switching modes of transportation for each node; determine the total waiting time of switching modes of transportation based on the waiting time of each node.

[0069] Secondly, as shown in Table 4 below, railway data, highway data, and river network data can be integrated to form multimodal transportation network data. Nodes need to be added at locations where transportation modes can be switched between different transportation network data, and information such as waiting time and cost of switching transportation modes should be added to the corresponding nodes (waiting time and generalized cost at nodes where there is no mode switching can be ignored).

[0070] Table 4. Examples of key node information in multimodal transportation network data

[0071] Node ID Waiting time Cost of switching methods 2 60 60 4 120 60 6 90 60

[0072] like Figure 3 As shown, the nodes with convertible transportation modes include nodes a, b, c, d, e, f, g, h, i, and j, where black dots represent nodes and blue lines represent edges; as shown... Figure 4 As shown, the journey from the city of origin (i.e., the starting point) to the destination port (i.e., the end point) involves both road-to-rail and rail-to-river transport nodes.

[0073] Step 1014: Determine the cumulative transportation cost based on the highway distance, the highway unit distance transportation cost, the railway distance, the railway unit distance transportation cost, the river network distance, the river network unit distance transportation cost, and the total cost of changing transportation modes;

[0074] In the process of converting a route into the required transportation cost, the transportation cost standards for different stages can be obtained based on existing regulations, standards, and current data. These stages include road transport routes, rail transport routes, inland waterway transport routes, road-to-rail, road-to-river, rail-to-road, and rail-to-river transport. Taking the originating city O and port D as an example, the journey from inland city O to seaport D may require one or more of the following modes of transport: road, rail, and river transport. Any path from O to D should be a complete and ordered transport path. Each ordered transport path includes one or more edges i from the transportation network data. When edge i is a road, the goods are transported by road, and the road distance is represented as d. i-road (i.e., road distance), road speed is expressed as v i-road The unit distance transportation cost by highway is expressed as c. i-road When edge i is a railway, goods are transported by rail, and the railway distance is represented as d. i-rail Railway speed is expressed as v i-rail The unit distance transportation cost of railways is expressed as c. i-rail When edge i is a river, goods are transported via river network, and the river network distance is represented as d. i-river River network velocity is represented by v i-river The unit distance transportation cost of the river network is expressed as c. i-river c j This represents the cost of changing the mode of transport at node j. If the mode of transport is not changed at node j, this cost is 0. The total cost of changing the mode of transport is expressed as... c o Indicates the cost at the origin of transportation; c d This represents the cost at the destination seaport. The cumulative transportation cost along a given route can be expressed as shown in formula (5):

[0075]

[0076] Among them, when the side is not a highway, d i-road When d is 0, it is not a railway. i-rail When d is 0, it is not an inland river. i-river The value is 0. j This represents the cost of changing the mode of transport at node j. If no mode of transport is changed at node j, this cost is 0. Generally, since the costs associated with the starting city O and the seaport D are similar, this cost can be ignored during the calculation process, depending on the actual situation. o and c d The cumulative transportation cost can be simplified to the following formula (6):

[0077]

[0078] Step 1015: Determine the cumulative time based on the highway time, the railway time, the river network time, and the total waiting time for changing modes of transportation.

[0079] In the process of converting path distance into the time cost required for the path, the speed standards corresponding to different types of transportation modes and the waiting time of corresponding links can be obtained based on existing relevant research and actual data.

[0080] t j This represents the waiting time for changing the mode of transport at node j. If the mode of transport is not changed at node j, then this time cost is 0; t o t represents the dwell time at the origin and destination of the transport; d The time spent at the destination seaport is represented by the road time, which can be calculated by dividing the road distance by the road speed or by directly calling the road time in Table 3. Similarly, the railway time can be calculated by dividing the railway distance by the railway speed or by directly calling the railway time in Table 3. The river network time can be calculated by dividing the river network distance by the river network speed or by directly calling the river network time in Table 3. Accordingly, the cumulative time through a certain transportation route can be expressed as shown in the following formula (7):

[0081]

[0082] For the same starting city t o The same, and the port stay time t d Similarly, in the calculation process, t can be ignored depending on the actual situation. o and t d The cumulative time can be simplified to the following formula (8):

[0083]

[0084] It should be noted that the speed of road transport is generally 80 km / h to 120 km / h, but the speed of road container truck freight transport is affected by many factors, and the average speed does not reach 80 km / h. Some studies that consider the speed of road transport containers include the time for loading or unloading container cargo and the waiting time in the yard in the total transport time, estimating the average speed of the truck over the whole journey to be about 60 km / h. Similarly, the average speed of rail transport over the whole journey can be estimated to be about 55 km / h, and the average speed of river network transport over the whole journey to be about 12 km / h.

[0085] Table 5 Average speed under different modes of transportation

[0086] Transportation methods average speed Road transport 60 km / h Railway transport 55 km / h Inland waterway transport 12M / h

[0087] In this embodiment, by integrating distance, time, and cost data from three modes of transportation—road, rail, and river network—a three-dimensional transportation network model covering "point-line-surface" is constructed, realizing full-scenario simulation of multimodal transport routes. By subdividing specific indicators for each mode of transportation (such as road unit distance cost and rail travel time), the crude estimation of traditional models with a "one-size-fits-all" approach is avoided. By identifying mode-of-transport conversion nodes, the waiting time and conversion costs during the conversion process are quantified. "Hidden losses" (such as efficiency reduction caused by multiple transfers) that are ignored in traditional models are included in the calculation, avoiding overestimation of efficiency during route planning.

[0088] In another exemplary embodiment of this application, such as Figure 5 As shown, the method for dividing the port hinterland also includes the following steps:

[0089] Step 109: Based on the weight of the goods from each originating city to each port and the total weight of the goods sent from the corresponding originating city to all ports, determine the actual probability of the corresponding originating city choosing each port.

[0090] Among them, by collecting actual freight data on passenger and freight flow, the actual probability of each departure city choosing different ports can be calculated, and the comprehensive attractiveness of different ports to specific departure cities can be calculated through the port selection probability model. This can represent the actual probability that the originating city O chooses the i-th port; m o-di Let represent the weight of the goods transported from the city of origin O to the i-th port. Let represent the total weight of goods sent from the originating city to all ports. Then, the actual probability of the originating city O choosing port i can be expressed by the following formula (9):

[0091]

[0092] It should be noted that if the sum of the actual probabilities of a certain origin city to all ports is not 1, the actual probabilities also need to be corrected to ensure that the sum of the actual probability values ​​of each city to different ports is 1. The corrected probabilities can be calculated using the following formula (10):

[0093]

[0094] in, This represents the probability that the originating city O will choose the i-th port after the correction. The actual probability of choosing the i-th port for the city of origin O. The sum of the actual probabilities of selecting all ports for the departure city O.

[0095] Step 110: Compare the actual probability and target probability of the departure city selecting each port to update the overall attractiveness of the corresponding port to the corresponding departure city.

[0096] Among them, the target probability P of the departure city choosing a port. o-di Theoretical probability, which is the model's predicted value, is used for theoretical analysis. These are actual statistical values ​​used for model validation and parameter back-calculation, by comparing P... o-di and It can identify model biases and optimize the port's overall attractiveness parameter A. di This allows for the prediction of the impact of policy changes (such as subsidies and infrastructure) on the hinterland. The comprehensive attractiveness A of the i-th port to the originating city O can be calculated by simultaneously applying formulas (3) and (9). di Update.

[0097] In this embodiment, the actual probability is calculated by the ratio of "the weight of goods sent from the originating city to a port" to "the total weight of goods sent from that city to all ports," directly reflecting the actual market selection behavior and avoiding the bias of relying solely on theoretical models. By comparing the actual probability with the target probability, the difference between theoretical predictions and market reality can be identified, and factors not considered in the model (such as implicit policy barriers and cargo owner preference inertia) can be discovered. Through the "data feedback-model correction" closed loop, the port attractiveness assessment system can be continuously optimized.

[0098] In another exemplary embodiment of this application, such as Figure 6 As shown, step 108 above can be replaced by steps 1081 to 1082:

[0099] Step 1081: If the target probability of selecting any port in any departure city is greater than the first probability threshold or the difference between the first maximum target probability and the second maximum target probability is greater than a preset difference, the corresponding departure city is determined as the advantageous hinterland of the corresponding port.

[0100] Among them, the target probability of selecting all ports for a certain shipping city can be determined and sorted, with the first largest target probability being the largest target probability and the second largest target probability being the second largest target probability.

[0101] Step 1082: If any departure city is not within the advantageous hinterland of any port, and the target probability of the corresponding departure city choosing any port is greater than the second probability threshold, then the corresponding departure city is determined as the competitive hinterland of the corresponding port.

[0102] For example, the first probability threshold can be 0.6, the preset difference can be 0.25, and the second probability threshold can be 0.1. For any city of origin, if there is a single port with a target probability greater than 0.6 or the difference between the first and second largest target probabilities is greater than 0.25, then the city of origin is the advantageous hinterland of the corresponding port. If there is a value greater than 0.1 in the target probability and the city of origin does not belong to the advantageous hinterland of a certain port, then it is divided into the competitive hinterland of multiple ports. Otherwise, the city of origin does not belong to the hinterland of any port.

[0103] In this embodiment of the application, probability thresholds and probability differences are used as quantification standards to achieve automated and precise division of the port's advantageous hinterland and competitive hinterland.

[0104] In another exemplary embodiment of this application, such as Figure 7 As shown, the method for dividing the port hinterland also includes the following steps:

[0105] Step 111: When the city of origin is a port's advantageous hinterland, strengthen the port's dependence on the advantageous hinterland through hardware upgrades and service extensions.

[0106] This can be achieved by upgrading port infrastructure, including but not limited to wharf expansion and intelligent transformation of loading and unloading equipment; and by extending services, such as establishing inland dry ports, optimizing customs clearance procedures, and providing integrated supply chain services, thereby enhancing the path dependence of the advantageous hinterland on the port.

[0107] Step 112: When the originating city is a competitive hinterland of the port, identify the bottleneck factors of the port's overall attractiveness to the originating city, and improve the transportation network data or feasible routes based on the bottleneck factors; adopt a differentiated pricing strategy and formulate tiered rates according to cargo type, transportation route, transportation time period, and cargo volume.

[0108] The bottleneck factors mentioned include, but are not limited to, insufficient transportation network coverage, high transportation costs, and limited feasible routes. Transportation network data can be optimized, including but not limited to opening new dedicated railway freight lines and optimizing inland waterway routes; expanding feasible routes, introducing multimodal transport modes, and increasing the combination of railway, highway, and waterway transport; for example, higher prices can be set for high-value-added goods such as precision instruments and electronic products, but paired with high-quality services (such as priority loading and unloading, and full temperature control); for low-value-added bulk goods such as coal and ore, discounted prices or bulk preferential prices can be set to improve total revenue through a balance between volume and price.

[0109] In this embodiment, when the probability of a port being selected by a city of origin is greater than a first probability threshold, or when the difference between the first and second highest probability of that port in that city is greater than a preset difference, the city is identified as a dominant hinterland. This helps ports quickly identify regions with high dependence and loyalty, allowing them to concentrate resources on infrastructure construction and service optimization, thus consolidating their dominant position in these regions. For example, ports can open more direct shipping routes and build dedicated logistics channels for their dominant hinterlands, further strengthening the hinterlands' dependence on the port. For cities of origin that are not dominant hinterlands of any port but have a probability of selecting a port greater than a second probability threshold, they are identified as competitive hinterlands. This definition method allows ports to clearly recognize regions with competitive relationships, and then formulate differentiated competitive strategies for different competitive hinterlands. For example, ports can enhance their attractiveness in competitive hinterlands by offering differentiated pricing and value-added services (such as providing better warehousing management and customs clearance services), thereby attracting cargo from competitors. The probability threshold and difference are adjustable parameters that can be flexibly modified according to factors such as the market environment and the port's development stage. When market competition intensifies or a port's own competitiveness improves, the hinterland can be redefined by adjusting thresholds. This ensures the redefined area always reflects reality, helping ports adjust their development strategies promptly and dynamically adapt to market changes. Clear hinterland delineation provides data support for regional economic planning and the coordinated development of port clusters. It allows for assessment of each port's reach and competitive landscape, avoiding redundant construction and cutthroat competition, and promoting division of labor and cooperation among ports. For example, when planning transportation routes, priority can be given to connecting advantageous hinterlands with ports, while simultaneously optimizing logistics networks in competing hinterlands to achieve efficient allocation of regional resources.

[0110] In another exemplary embodiment of this application, such as Figure 8 As shown, the method for dividing the port hinterland also includes the following steps:

[0111] Step 113: Update the traffic network data as infrastructure improves;

[0112] Infrastructure improvement can refer to upgrading transportation hardware facilities in ports or hinterlands, such as building or expanding railway / highway trunk lines, bridges, and tunnels; upgrading the grade of terminal berths (e.g., to accommodate larger tonnage vessels); intelligently transforming port loading and unloading equipment (e.g., automated container terminals); and updating transportation network data according to changes in infrastructure.

[0113] Step 114: If the dedicated railway line is open, update the feasible path;

[0114] Among them, the opening of dedicated railway lines specifically refers to the construction of dedicated railway lines to enhance the port's collection and distribution capacity, such as: freight lines that directly connect the port from the hinterland industrial park / mining area (such as "port-rail intermodal lines"); branch railways that connect with the national railway network to alleviate the pressure on the main lines. With the opening of dedicated railway lines, feasible routes may be updated. For example, if the original feasible route was "road plus sea", now the combination of "dedicated railway line plus sea" is added.

[0115] Step 115: In the case of freight rate subsidies, based on the subsidy strategy, deduct the freight rate subsidy corresponding to each feasible path from the generalized cost of each feasible path.

[0116] Among them, freight rate subsidies can be price discounts offered by ports to attract cargo and support specific transportation businesses (such as green transportation and multimodal transport). For example, "ton-kilometer freight subsidies" are given to goods transported via dedicated railway lines; fuel cost subsidies are given to road transport sections using new energy trucks.

[0117] In this embodiment, a dynamic update mechanism ensures the timeliness and accuracy of port hinterland delineation: transportation network data is updated after infrastructure improvements, reflecting real-time changes in transport efficiency; the opening of dedicated railway lines expands feasible routes, enhancing the flexibility of multimodal transport; and cost discounts under freight rate subsidies accurately quantify the policy's impact on cargo owners' choices. These three factors collectively help the port optimize resource allocation based on real-time data, enhancing its attractiveness and competitiveness to hinterland cargo sources.

[0118] In this embodiment, a technical framework for port hinterland identification and classification is constructed, which integrates multi-source data such as actual freight data, road network data, and freight rate data. It takes into account the current situation of port hinterland selection and the fine process of multimodal transport, and realizes accurate identification of port hinterland under different scenarios (including railway line opening scenarios, freight rate subsidy scenarios, etc.), effectively supporting the port's pricing optimization and precise improvement needs.

[0119] This solution achieves port hinterland division under multimodal transport. Existing technical solutions either compare different modes based on the cost of a single mode or combine multimodal transport at the grid level, which cannot fit the actual scenario of multimodal transport mode changes. This solution, through the construction of a transport network, clarifies specific mode switching points, which is more in line with the actual situation.

[0120] The cost measurement method is refined based on the actual transportation process to achieve more accurate hinterland identification. First, it considers not only route costs but also node costs (mainly waiting time and costs for changing modes of transportation); second, it comprehensively considers transportation costs and time costs, which is more in line with the actual cost content that freight transportation focuses on.

[0121] Breaking through the limitations of a static perspective, this study solves the hinterland model based on the current situation. By considering key factors in a dynamic market environment, different scenario modes are set up to simulate the evolution of the hinterland under dynamic market conditions, enabling multi-scenario comparison and supporting the accurate identification of port hinterlands and the formulation of optimization measures under different future scenarios.

[0122] Based on the same inventive concept, this application also provides a port hinterland delineation device for implementing the port hinterland delineation method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more port hinterland delineation device embodiments provided below can be found in the limitations of the port hinterland delineation method described above, and will not be repeated here.

[0123] In one exemplary embodiment, such as Figure 9 As shown, a port hinterland delineation device 200 includes:

[0124] The first acquisition module 201 is used to acquire the cumulative transportation cost, cumulative time and time value of each segment of the transportation route in all feasible routes from each originating city to each port. The time value is the value loss of the goods per unit time. The feasible routes include at least one of road, rail and river network transportation. The cumulative transportation cost includes the total cost of changing transportation modes. The cumulative time includes the total waiting time for changing transportation modes.

[0125] The first determining module 202 is used to determine the minimum generalized cost from each of the originating cities to each of the ports based on the cumulative transportation cost, the cumulative time, and the time value of all feasible routes.

[0126] The second determining module 203 is used to determine the target probability of a corresponding departure city choosing each of the ports based on the minimum generalized cost from any of the departure cities to each of the ports and the comprehensive attractiveness of each port to the corresponding departure city.

[0127] The partitioning module 204 is used to partition the hinterland of each port based on the target probability of selecting each port from each departure city.

[0128] As an optional implementation, the device further includes: a second acquisition module for acquiring location data of all ports and all cities within the target area; a construction module for constructing transportation network data based on the location data, the transportation network data including highway data, railway data, and river network data, the highway data including highway distance, highway time, and highway unit distance transportation cost, the railway data including railway distance, railway time, and railway unit distance transportation cost, and the river network data including river network distance, river network time, and river network unit distance transportation cost; and a third determination module for determining nodes in the transportation network data that can switch modes of transportation, and adding a waiting time for switching modes of transportation to each node. The system comprises: a first determination module for determining the cost of switching transportation modes; a second determination module for determining the total cost of switching transportation modes based on the cost of switching transportation modes at each node; a third determination module for determining the total waiting time of switching transportation modes based on the waiting time of switching transportation modes at each node; a fourth determination module for determining the cumulative transportation cost based on the road distance, the road unit distance transportation cost, the railway distance, the railway unit distance transportation cost, the river network distance, the river network unit distance transportation cost, and the total cost of switching transportation modes; and a fifth determination module for determining the cumulative time based on the road time, the railway time, the river network time, and the total waiting time of switching transportation modes.

[0129] As an optional implementation, the apparatus further includes: a sixth determining module, configured to determine the actual probability of a corresponding originating city choosing each of the ports based on the weight of the goods from each originating city to each of the ports and the total weight of the goods sent from the corresponding originating city to all ports; and an updating module, configured to compare the actual probability of an originating city choosing each of the ports with the target probability, so as to update the overall attractiveness of the corresponding port to the corresponding originating city.

[0130] As an optional implementation, the partitioning module 204 includes: a first partitioning submodule, used to determine the corresponding departure city as the advantageous hinterland of the corresponding port when the target probability of any departure city selecting any of the ports is greater than a first probability threshold, or the difference between the first maximum target probability and the second maximum target probability is greater than a preset difference; and a second partitioning submodule, used to determine the corresponding departure city as the competitive hinterland of the corresponding port when any departure city is not the advantageous hinterland of any port and the target probability of the corresponding departure city selecting any port is greater than a second probability threshold.

[0131] As an optional implementation, the device further includes: a reinforcement module, used to enhance the port's dependence on the port through hardware upgrades and service extensions when the originating city is a port's advantageous hinterland; an improvement module, used to identify bottleneck factors in the port's overall attractiveness to the originating city when the originating city is a port's competitive hinterland, and improve transportation network data or feasible routes based on the bottleneck factors; and a differentiated pricing strategy, which sets tiered rates based on cargo type, transportation route, transportation time, and cargo volume.

[0132] As an optional implementation, the first determining module 202 includes: a first determining submodule, used to determine the generalized cost corresponding to each feasible path based on the cumulative transportation cost, the cumulative time, and the time value of all feasible paths; and a second determining submodule, used to determine the minimum generalized cost from each of the originating cities to each of the ports based on a shortest path search algorithm.

[0133] As an optional implementation, the apparatus further includes: a first update module for updating the transportation network data when infrastructure is improved; a second update module for updating the feasible routes when a dedicated railway line is opened; and a deduction module for deducting the fare subsidy corresponding to each feasible route from the generalized cost of each feasible route based on a subsidy strategy when a fare subsidy is provided.

[0134] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 10 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When executed by the processor, the computer program implements a method for dividing the hinterland of a port.

[0135] Those skilled in the art will understand that Figure 10The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0136] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0137] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0138] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0140] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0141] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0142] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0143] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for dividing a port hinterland, characterized in that, The methods for dividing the port hinterland include: The cumulative transportation cost, cumulative time, and time value of each segment of the transportation route are obtained from each originating city to each port. The time value is the value loss of the goods per unit time. The feasible routes include at least one of road, rail, and river network transportation. The cumulative transportation cost includes the total cost of changing modes of transportation. The cumulative time includes the total waiting time for changing modes of transportation. Based on the cumulative transportation costs, cumulative time, and time value of all feasible routes, determine the minimum generalized cost from each of the originating cities to each of the ports; Based on the minimum generalized cost from any of the aforementioned departure cities to each of the aforementioned ports and the overall attractiveness of each of the aforementioned ports to the corresponding departure city, the target probability for the corresponding departure city to choose each of the aforementioned ports is determined according to the following port selection probability model: ； in, Indicates the starting city O is selected as the first i The target probability of each port; For the first i The overall attractiveness of each port to the departure city O; From the starting city O to the first i The minimum generalized cost of a port, where β is the friction coefficient of the generalized cost; Based on the target probability of selecting each port from each departure city, the hinterland of each port is divided. Based on the weight of the goods from each originating city to each port and the total weight of the goods sent from the corresponding originating city to all ports, the actual probability of the corresponding originating city choosing each port is determined according to the following formula: ； in, Indicates the starting city O is selected as the first i The actual probability of each port Indicates from the starting city O to the... i The weight of goods at each port. This represents the total weight of goods sent from city O to all ports. n Total number of ports; Compare the actual probability and target probability of the departure city choosing each of the aforementioned ports to update the overall attractiveness of the corresponding port to the corresponding departure city: Comparison and , identify port selection probability model deviation, optimize the comprehensive attractiveness parameters of the port .

2. The method for dividing a port hinterland according to claim 1, characterized in that, The method for dividing the port hinterland also includes: Obtain location data for all ports and cities within the target area; Based on the location data, traffic network data is constructed, which includes highway data, railway data, and river network data. The highway data includes highway distance, highway time, and highway unit distance transportation cost. The railway data includes railway distance, railway time, and railway unit distance transportation cost. The river network data includes river network distance, river network time, and river network unit distance transportation cost. Identify nodes in the traffic network data that can switch modes of transportation, and add the waiting time and cost of switching modes of transportation to each node; determine the total cost of switching modes of transportation based on the cost of switching modes of transportation at each node; determine the total waiting time of switching modes of transportation based on the waiting time of switching modes of transportation at each node. The cumulative transportation cost is determined based on the road distance, the road unit distance transportation cost, the railway distance, the railway unit distance transportation cost, the river network distance, the river network unit distance transportation cost, and the total cost of changing transportation modes. The cumulative time is determined based on the road time, the railway time, the river network time, and the total waiting time for switching modes of transport.

3. The method of dividing a port hinterland according to claim 1, characterized in that, The step of dividing the hinterland of each port based on the target probability of selecting each port from each departure city includes: If the target probability of selecting any port in any departure city is greater than the first probability threshold, or if the difference between the first and second target probabilities is greater than a preset difference, the corresponding departure city will be determined as the advantageous hinterland of the corresponding port. If any departure city is not within the advantageous hinterland of any port, and the probability of the corresponding departure city choosing any port is greater than the second probability threshold, then the corresponding departure city is identified as the competitive hinterland of the corresponding port.

4. The method of claim 1, wherein, The method for dividing the port hinterland also includes: With the departure city serving as a port's advantageous hinterland, the port's dependence on the port can be strengthened through hardware upgrades and service extensions. When the originating city is a competitive hinterland of the port, identify the bottleneck factors that make the port attractive to the originating city. Based on these bottleneck factors, improve transportation network data or feasible routes. Adopt a differentiated pricing strategy and formulate tiered rates based on cargo type, transportation route, transportation time, and cargo volume.

5. The method of dividing a port hinterland according to claim 1, characterized in that, Determining the minimum generalized cost from each of the originating cities to each of the ports, based on the cumulative transportation costs, cumulative time, and time value of all feasible routes, includes: Based on the cumulative transportation cost, cumulative time, and time value of all feasible paths, determine the generalized cost corresponding to each feasible path; Based on the shortest path search algorithm, the minimum generalized cost from each of the aforementioned departure cities to each of the aforementioned ports is determined.

6. The method for dividing a port hinterland according to claim 5, characterized in that, The method for dividing the port hinterland also includes: The traffic network data is updated as infrastructure improves. The feasible routes will be updated once the dedicated railway line is operational. In the case of freight rate subsidies, based on the subsidy strategy, the freight rate subsidy corresponding to each feasible path is deducted from the generalized cost of each feasible path.

7. A device for dividing a port hinterland, characterized in that, The port hinterland delineation device includes: The first acquisition module is used to acquire the cumulative transportation cost, cumulative time and time value of each segment of the transportation route in all feasible routes from each originating city to each port. The time value is the value loss of the goods per unit time. The feasible routes include at least one of road, rail and river network transportation. The cumulative transportation cost includes the total cost of changing transportation modes. The cumulative time includes the total waiting time for changing transportation modes. The first determining module is used to determine the minimum generalized cost from each of the originating cities to each of the ports based on the cumulative transportation costs, cumulative time and time value of all feasible routes. The second determining module is used to determine the target probability of a corresponding departure city choosing each of the ports based on the minimum generalized cost from any of the departure cities to each of the ports and the comprehensive attractiveness of each port to the corresponding departure city, according to the following port selection probability model: ； in, Indicates the starting city O is selected as the first i The target probability of each port; For the first i The overall attractiveness of each port to the departure city O; From the starting city O to the first i The minimum generalized cost of a port, where β is the friction coefficient of the generalized cost; The partitioning module is used to partition the hinterland of each port based on the target probability of selecting each port for each departure city. The sixth determining module is used to determine the actual probability of a corresponding originating city selecting each port based on the weight of the goods from each originating city to each port and the total weight of the goods sent from the corresponding originating city to all ports, according to the following formula: ； wherein, denotes the actual probability of the city of origin O to select the i port number i, denotes the weight of the goods from the city of origin O to the i port number i, denotes the sum of the weights of the goods sent from the city of origin O to all ports, n is the total number of ports; The update module compares the actual probability and target probability of a shipping city choosing each port to update the overall attractiveness of the corresponding port to the corresponding shipping city. Comparing and , identifying port selection probability model deviation, optimizing the comprehensive attractiveness parameter of the port .

8. A computer device comprising: The memory and processor contain a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method for dividing the port hinterland according to any one of claims 1-6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method for dividing the port hinterland as described in any one of claims 1-6.

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