A ship replenishment route generation method and device based on graph optimization

Abstract

The application discloses a ship supply route generation method and device based on graph optimization, and the method comprises the following steps: collecting a material demand information set, a material supply information set and a ship transportation capacity information set; the material demand information set comprises each task point information and corresponding material demand information; the material demand information comprises the demand quantity, the demand urgency and the transportation requirement information of each type of material; the task point information comprises the task point position coordinates and the safe storage capacity index; the material demand information set and the material supply information set are subjected to optimization matching processing to obtain a material supply route information set; based on the material supply route information set and a real-time collected sea state information set, the ship transportation capacity information set is subjected to planning processing to obtain a ship supply route information set.

Description

Technical Field

[0001] This invention relates to the fields of resource allocation, industrial data processing, and strategy optimization, specifically to a method and apparatus for generating ship replenishment routes based on graph optimization. Background Technology

[0002] In various maritime activities such as maritime transport and ocean-going operations, ship replenishment is a crucial link in ensuring the continuous progress of missions and operational safety. The scientific planning of ship replenishment routes directly affects replenishment efficiency, reliability of material support, and navigation safety. With the increasing complexity and diversification of maritime missions, the material needs at mission points are characterized by multiple categories, differentiation, and high urgency. The material supply capacity of supply points also varies significantly. At the same time, the complex and changeable marine environment and real-time sea conditions have a significant impact on ship navigation and replenishment operations. Traditional methods for generating ship replenishment routes are no longer sufficient to meet practical application needs.

[0003] Currently, existing ship replenishment route planning technologies have significant limitations: some methods simply consider the distance between supply points and mission points, failing to fully integrate the urgency of material needs, the stable supply capacity of supply points, the safe storage capacity of mission points, and the transportation requirements of the materials themselves. This results in planned replenishment routes that cannot guarantee the sufficiency and reliability of material supply, easily leading to material shortages or supply redundancy, thus affecting mission execution. While some methods consider certain material and ship-related factors, they fail to uniformly process parameters of different dimensions, resulting in ineffective parameter calculations, biased optimization results, and difficulty in maximizing supply efficiency.

[0004] Furthermore, existing technologies often overlook the impact of real-time sea state information on ship replenishment routes, failing to accurately match a ship's sea state adaptability with real-time sea conditions. This may result in ships being assigned to routes beyond their capabilities, increasing navigational safety risks and even delaying replenishment opportunities. Simultaneously, the lack of precise matching between ship transport capacity and cargo transport requirements during route planning easily leads to wasted or insufficient ship capacity. Moreover, the lack of systematic optimization of replenishment routes and ship allocation makes it difficult to balance multiple objectives such as replenishment efficiency, navigational safety, and cost control, and thus cannot adapt to the complex and ever-changing needs of maritime replenishment scenarios. Therefore, developing a ship replenishment route generation method that can comprehensively consider multiple factors and achieve precise optimization has become an urgent technical problem to be solved. Summary of the Invention

[0005] This invention addresses the problem that existing ship replenishment route planning technologies only consider the distance between supply points and mission points, failing to fully integrate the urgency of material needs, the stable supply capacity of supply points, the safe storage capacity of mission points, and the transportation requirements of the materials themselves. This results in planned replenishment routes that cannot ensure the sufficiency and reliability of material supply, easily leading to material shortages or supply redundancy. This invention discloses a ship replenishment route generation method and apparatus based on graph optimization.

[0006] In a first aspect, this invention discloses a method for generating ship replenishment routes based on graph optimization, comprising: S1, collect a set of material demand information, a set of material supply information, and a set of ship transportation capacity information; the set of material demand information includes information on each task point and the corresponding material demand information; the material demand information includes the demand quantity, urgency of demand, and transportation requirements of each type of material; the task point information includes the task point location coordinates and safe storage capacity indicators. The material supply information set includes information on each supply point and corresponding material supply information; the supply point information includes the location coordinates of the supply point and stable supply capacity indicators; the material supply information includes the inventory quantity and indicator completeness of each type of material; the transportation requirement information includes several transportation capacity indicator requirement values. The set of ship transport capacity information includes all transport capacity index values ​​and sea state adaptability values ​​for each ship; S2, perform optimization matching on the set of material demand information and the set of material supply information to obtain a set of material supply route information; S3. Based on the set of material supply route information and the set of sea condition information collected in real time, the set of ship transportation capacity information is planned and processed to obtain the set of ship replenishment route information.

[0007] The optimization and matching process of the set of material demand information and the set of material supply information to obtain a set of material supply route information includes: S21, Perform material supply satisfaction screening on the set of material demand information and the set of material supply information to obtain a preliminary set of supply route information. S22, perform supply efficiency optimization processing on the preliminary supply route information set to obtain the material supply route information set.

[0008] The process of performing supply satisfaction screening on the set of material demand information and the set of material supply information to obtain a preliminary supply route information set includes: S211, Based on the material demand information set and the material supply information set, calculate the pre-selected supply route information to obtain the pre-selected supply route information set; S212, based on the set of material demand information and the set of material supply information, with the goal of ensuring sufficient material supply, the set of pre-selected supply route information is filtered to obtain a preliminary set of supply route information.

[0009] The calculation of pre-selected supply route information based on the set of material demand information and the set of material supply information, to obtain the set of pre-selected supply route information, includes: S2111, for each task point in the material demand information set, the supply point information in the material supply information set is filtered according to its corresponding material demand information to obtain the corresponding pre-selected supply route; the pre-selected supply route includes the task point and the corresponding supply point. S2112, using the pre-selected supply routes based on all task point information, construct a set of pre-selected supply routes; S2113, calculate the pre-selected supply route information for the pre-selected supply routes in the pre-selected supply route set to obtain a pre-selected supply route information set; the pre-selected supply route information set includes several pre-selected supply route information.

[0010] The expression for calculating the pre-selected supply route information is as follows: , , Where r is the distance of the pre-selected supply route, To ensure redundancy in the pre-selected supply routes, and These represent the safe storage capacity index of the task point and the stable supply capacity index of the supply point on the pre-selected supply route, respectively. (x1, y1) and (x2, y2) are the location coordinates of the task point and the supply point on the pre-selected supply route, respectively. and These are the bias factors for the preset safe storage capacity index and stable supply capacity index, respectively, and their values ​​are not 0; the distance and redundancy of the pre-selected supply route together constitute the pre-selected supply route information.

[0011] Based on the set of material demand information and the set of material supply information, and with the goal of ensuring sufficient material supply, the set of pre-selected supply route information is filtered to obtain a preliminary set of supply route information, including: S2121, Based on the aforementioned set of material demand information and set of material supply information, a material supply sufficiency screening model is constructed with the objective of material supply sufficiency. The expression for the material supply sufficiency screening model is as follows: , , , , , in, The selection factor for the i-th pre-selected supply route in the set of pre-selected supply route information is defined as follows: a value of 1 indicates that the pre-selected supply route is selected, and a value of 0 indicates that the pre-selected supply route is not selected. The value represents the sufficiency of material supply. The preset sufficiency threshold, , and These are the preset distance threshold, redundancy threshold, and total number of routes threshold, respectively. Q represents the total number of pre-selected supply routes, and K represents the total number of material categories. and Let be the inventory of the k-th type of material at the supply point of the i-th pre-selected supply route information and the demand for the k-th type of material at the task point, respectively. and These represent the distance and redundancy of the i-th pre-selected supply route information, respectively. S2122, using the pre-selected supply route information set as the solution set, the material supply adequacy screening model is solved to obtain a preliminary supply route information set; the preliminary supply route information set includes several feasible solutions; the feasible solution is a combination of selection factors that satisfy the material supply adequacy screening model; the combination of selection factors is a combination of selection factors corresponding to all pre-selected supply route information.

[0012] The process of optimizing the supply route information set to obtain a new material supply route information set includes: S221, Based on the aforementioned set of material supply information and set of material demand information, a supply efficiency optimization model is constructed; the expression of the supply efficiency optimization model is: ， , , in, Let be the factor vector to be solved. , For the supply efficiency function, The selection factor for the j-th preliminary supply route in the preliminary supply route information set is defined as follows: a value of 1 indicates that the preliminary supply route is selected, and a value of 0 indicates that the preliminary supply route is not selected. The distance for the j-th initial supply route information. and These represent the urgency of demand for category k materials at the task point in the j-th preliminary supply route information and the completeness of indicators for category k materials at the supply point in the j-th preliminary supply route information, respectively. The total number of supply routes. , and These are preset weighting factors, and all three are greater than 0; S222, Solve the supply efficiency optimization model to obtain the solution values ​​of the factor vector; S223, Select the corresponding preliminary supply route information from the preliminary supply route information set according to the solution value of the factor vector, and construct the material supply route information set.

[0013] A second aspect of the present invention discloses a graph-optimized ship replenishment route generation device, the device comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the graph-optimized ship resupply route generation method.

[0014] In a third aspect of this invention, a computer-readable storage medium is disclosed, the computer-readable storage medium storing computer instructions, which, when invoked by a computer, are used to execute the graph-optimized ship replenishment route generation method.

[0015] In a fourth aspect of this invention, an information data processing terminal is disclosed, which is used to implement the graph-optimized ship replenishment route generation method described above.

[0016] The beneficial effects of this invention are as follows: This invention achieves comprehensive coverage of multi-dimensional information related to replenishment by comprehensively collecting various information related to material demand, material supply, and ship transportation capacity, including the location and capacity indicators of mission points and supply points, details of material demand and supply, and the transportation capacity and sea condition adaptability of ships. This provides complete and accurate data support for subsequent route optimization planning and effectively solves the problem of unreasonable routes caused by incomplete information collection and insufficient planning basis in existing technologies.

[0017] Before performing optimization matching, this invention performs dimensionless processing on various related variables, effectively eliminating computational barriers between parameters with different dimensions, ensuring that various parameters can be effectively integrated and calculated, improving the solution accuracy of the optimization model, avoiding planning deviations caused by differences in dimensions, and making the subsequent supply matching and route planning results more scientific and reliable.

[0018] This invention optimizes the matching of material demand and supply in steps. First, it obtains a preliminary supply route by screening the material supply satisfaction, and then obtains the optimal material supply route by optimizing the supply efficiency. This ensures that the material supply can meet the actual needs of the task point and guarantees the sufficiency of the material supply, while maximizing the supply efficiency. It effectively balances the relationship between supply reliability and efficiency and solves the problem that existing technologies cannot take both into account.

[0019] This invention, by constructing a scientific optimization model and employing a suitable solution algorithm, can quickly obtain the optimal set of ship replenishment routes. This not only improves the efficiency of route planning but also takes into account multiple objectives such as replenishment efficiency, navigation safety, and cost control. It is applicable to maritime replenishment scenarios of different scales and complexities, and has strong practicality and scalability. It can effectively replace traditional route planning methods and provide efficient and reliable technical support for maritime replenishment operations. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention. Detailed Implementation

[0021] To better understand the content of this invention, an embodiment is provided here.

[0022] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention.

[0023] In a first aspect, this invention discloses a method for generating ship replenishment routes based on graph optimization, comprising: S1 collects a set of information on material demand, a set of information on material supply, and a set of information on ship transportation capacity. The set of material demand information includes information on each task point and corresponding material demand information; the material demand information includes the demand quantity, urgency of demand, and transportation requirements for each type of material; the task point information includes the location coordinates of the task point and the safe storage capacity index. The material supply information set includes information on each supply point and corresponding material supply information; the supply point information includes the location coordinates of the supply point and stable supply capacity indicators; the material supply information includes the inventory quantity and indicator completeness of each type of material; the transportation requirement information includes several transportation capacity indicator requirement values. The set of ship transport capacity information includes all transport capacity index values ​​and sea state adaptability values ​​for each ship; S2, perform optimization matching on the set of material demand information and the set of material supply information to obtain a set of material supply route information; S3. Based on the set of material supply route information and the set of sea condition information collected in real time, the set of ship transportation capacity information is planned and processed to obtain the set of ship replenishment route information.

[0024] The transportation requirements information refers to the required values ​​of each type of transportation capacity index of the ship for the materials, and there is a one-to-one correspondence between the materials and the ship's transportation capacity index values. The task point is the location where materials are needed to perform a specific task; the supply point is the location where materials are stored and supplied; the safe storage capacity index is calculated based on indicators such as the completeness and failure rate of historically stored materials at the task point; the stable supply capacity index is calculated based on indicators such as historical stable supply data of materials at the supply point and material generation capacity data of surrounding areas; the calculation can be a weighted calculation. The index completeness is obtained by collecting various indicators of materials and calculating the differences with corresponding standard indicators; Before performing step S2, to ensure effective calculations between variables of different dimensions, the relevant variables in the sets of material demand information, material supply information, and ship transportation capacity information were dimensionless. This dimensionless processing can be performed using a normalization method.

[0025] The optimization and matching process of the set of material demand information and the set of material supply information to obtain a set of material supply route information includes: S21, Perform material supply satisfaction screening on the set of material demand information and the set of material supply information to obtain a preliminary set of supply route information. S22, perform supply efficiency optimization processing on the preliminary supply route information set to obtain the material supply route information set.

[0026] The process of performing supply satisfaction screening on the set of material demand information and the set of material supply information to obtain a preliminary supply route information set includes: S211, Based on the material demand information set and the material supply information set, calculate the pre-selected supply route information to obtain the pre-selected supply route information set; S212, based on the set of material demand information and the set of material supply information, with the goal of ensuring sufficient material supply, the set of pre-selected supply route information is filtered to obtain a preliminary set of supply route information.

[0027] The calculation of pre-selected supply route information based on the set of material demand information and the set of material supply information, to obtain the set of pre-selected supply route information, includes: S2111, for each task point in the material demand information set, the supply point information in the material supply information set is filtered according to its corresponding material demand information to obtain the corresponding pre-selected supply route; the pre-selected supply route includes the task point and the corresponding supply point. S2112, using the pre-selected supply routes based on all task point information, construct a set of pre-selected supply routes; S2113, calculate the pre-selected supply route information for the pre-selected supply routes in the pre-selected supply route set to obtain a pre-selected supply route information set; the pre-selected supply route information set includes several pre-selected supply route information.

[0028] The expression for calculating the pre-selected supply route information is as follows: , , Where r is the distance of the pre-selected supply route, To ensure redundancy in the pre-selected supply routes, and These represent the safe storage capacity index of the task point and the stable supply capacity index of the supply point on the pre-selected supply route, respectively. (x1, y1) and (x2, y2) are the location coordinates of the task point and the supply point on the pre-selected supply route, respectively. and These are bias factors for the preset safe storage capacity index and stable supply capacity index, respectively. Their values ​​are not zero and can be obtained by calculating the average of all indices. The distance and redundancy of the pre-selected supply routes together constitute the pre-selected supply route information.

[0029] The process involves filtering the supply point information in the material supply information set based on the corresponding material demand information for each task point in the material demand information set to obtain a corresponding pre-selected supply route. This process also involves filtering the supply point information for each task point in the material demand information set based on the demand for all materials in its corresponding material demand information, ensuring that the inventory of all materials is greater than the demand for the corresponding materials. The task point and the supply point are then used as the pre-selected supply route.

[0030] Based on the set of material demand information and the set of material supply information, and with the goal of ensuring sufficient material supply, the set of pre-selected supply route information is filtered to obtain a preliminary set of supply route information, including: S2121, Based on the aforementioned set of material demand information and set of material supply information, a material supply sufficiency screening model is constructed with the objective of material supply sufficiency. The expression for the material supply sufficiency screening model is as follows: , , , , , in, The selection factor for the i-th pre-selected supply route in the set of pre-selected supply route information is defined as follows: a value of 1 indicates that the pre-selected supply route is selected, and a value of 0 indicates that the pre-selected supply route is not selected. The value represents the sufficiency of material supply. The preset sufficiency threshold, , and These are the preset distance threshold, redundancy threshold, and total number of routes threshold, respectively. Q represents the total number of pre-selected supply routes, and K represents the total number of material categories. and Let be the inventory of the k-th type of material at the supply point of the i-th pre-selected supply route information and the demand for the k-th type of material at the task point, respectively. and These represent the distance and redundancy of the i-th pre-selected supply route information, respectively. All selection factors are variables to be solved, and their values ​​are 0 or 1; S2122, using the pre-selected supply route information set as the solution set, the material supply sufficiency screening model is solved to obtain a preliminary supply route information set. The preliminary supply route information set includes several feasible solutions; each feasible solution is a combination of all selection factors that satisfy the material supply sufficiency screening model; each selection factor combination is a combination of selection factors corresponding to all pre-selected supply route information. The solution to the material supply sufficiency screening model can be obtained by exhaustive search, which involves arbitrarily combining the selection factors of all pre-selected supply route information to select the combination of each selection factor that satisfies the material supply sufficiency screening model as a feasible solution. The process of optimizing the supply route information set to obtain a new material supply route information set includes: S221, Based on the aforementioned set of material supply information and set of material demand information, a supply efficiency optimization model is constructed; the expression of the supply efficiency optimization model is: ， , , in, Let be the factor vector to be solved. , For the supply efficiency function, The selection factor for the j-th preliminary supply route in the preliminary supply route information set is defined as follows: a value of 1 indicates that the preliminary supply route is selected, and a value of 0 indicates that the preliminary supply route is not selected. The distance for the j-th initial supply route information. and These represent the urgency of demand for category k materials at the task point in the j-th preliminary supply route information and the completeness of indicators for category k materials at the supply point in the j-th preliminary supply route information, respectively. The total number of supply routes. , and These are preset weighting factors, and all three are greater than 0; S222, Solve the supply efficiency optimization model to obtain the solution values ​​of the factor vector; S223, using the solution value of the factor vector, select the corresponding preliminary supply route information from the preliminary supply route information set to construct the material supply route information set.

[0031] The solution to the supply efficiency optimization model can be achieved using optimization model solving algorithms, such as genetic algorithms or numerical search algorithms.

[0032] The process of planning and processing the ship transport capacity information set based on the material supply route information set and the real-time collected sea state information set yields a ship replenishment route information set, including: S31, Based on the material supply route information set, the sea condition is collected in real time for each supply route to obtain a sea condition information set; the sea condition information set includes the sea condition information of each supply route; S32, Based on the set of material supply route information, sea condition information and ship transport capacity information, a supply route optimization model is constructed; S33, Solve the supply route optimization model to obtain a set of ship supply route information.

[0033] The replenishment route optimization model, constructed based on the set of material supply route information, sea state information, and ship transport capacity information, includes: S321, based on the set of material supply route information, constructs a supply network diagram and a decision variable matrix. Abstract the supply task into a directed weighted graph. Vertex set It is the set of all supply points and task points included in the material supply route information set. This is the set of supply points, corresponding to the coordinates of the supply point locations mentioned above. This is the set of task points, corresponding to the coordinates of the task points mentioned above. Edge set. : Represents the potential path for a ship to move between vertices. The weights of the edges are determined by real-time sea state information (wind, waves, current) and distance. Define a three-dimensional 0-1 decision variable matrix. This is used to represent the allocation relationship between ships, supply routes, and supply tasks. Assume... This represents the total number of available vessels (from a collection of vessel transport capacity information). The total number of planned voyage missions (determined based on the set of material supply route information). This represents the total number of material categories. (Definition) Decision variables in as follows: in, .

[0034] S322, Based on the Decision Variable Matrix A target function is constructed; the target function is to maximize the net benefit between the ship's transport capacity and the cargo transport requirements. Here, the net benefit is defined as the ship's transport capacity index under a specific sea state minus the cargo transport requirements.

[0035] objective function The expression is: in, Assign matrix elements to the three dimensions defined above. To indicate the first ship to the first The transport capacity index values ​​for this type of goods are derived from a collection of ship transport capacity information. Indicates the first The first of the material supply routes The required transport capacity indicators for this type of material are derived from the set of material demand information. These are preset weighting coefficients used to balance the dimensions and priorities between capacity utilization and demand fulfillment.

[0036] S323, Based on the supply network graph, constraints are constructed; the constraints include: (1) Task uniqueness constraint, which means that among all supply routes, a ship can only participate in the transportation of one type of material in one supply route. Its expression is: (2) Ship capacity and load constraints, used to indicate the constraints for each ship In all its allocated supply routes, the total amount of supplies it carries cannot exceed its physical limit; in graph theory, this is equivalent to flowing through nodes. The traffic limit is expressed as: in, For the first The unit volume and weight of this type of material. For the first The maximum cargo hold capacity and deadweight of a vessel. The unit volume and weight of cargo are included in the transport capacity index requirements; the maximum cargo hold capacity and deadweight of a vessel are part of the vessel's transport capacity index.

[0037] (3) Vessel sea state adaptability constraint, used to indicate that a vessel can only be assigned to a route permitted by its sea state adaptability value, assuming For ships Sea state adaptation value, For the supply route Given the sea state information, the expression for the ship's sea state adaptability constraint is: If the sea conditions along a supply route are too severe, exceeding the ship's tolerance threshold, then The value is set to 0. The sea state adaptability value of a vessel is a component of its transport capacity index.

[0038] (4) Time window constraint, meaning that materials must be delivered within the time allowed by the urgency of demand. Let... For the current time, For ships Implementing material supply routes The estimated travel time (calculated using a graph shortest path algorithm on the supply network graph): , in, Indicates the first The latest delivery time of supplies to each task point is calculated based on the urgency of the need, and its calculation expression can be: . The preset time constant factor, The urgency of the need for supplies at the m-th task point.

[0039] S324. Using the objective function and constraints, a supply route optimization model is constructed.

[0040] The decision variable matrix is ​​obtained by solving the supply route optimization model. Simulated annealing, genetic algorithms, shortest path algorithms, or minimum spanning tree algorithms in graph theory can be used.

[0041] Solving the replenishment route optimization model to obtain the ship replenishment route information set involves solving the replenishment route optimization model to obtain the decision variable matrix. According to the decision variable matrix The system identifies the ships and types of supplies corresponding to each supply route in the supply route information set. Using all the ships and types of supplies corresponding to all supply routes, a ship replenishment route information set is constructed.

[0042] The real-time sea condition data can be obtained by crawling data from marine meteorological websites, based on the supply route.

[0043] In all embodiments of the present invention, the variables involved in all computational expressions or mathematical functions have been dimensionlessized before computation.

[0044] In all embodiments of the present invention, the values ​​of the independent variables in the input of all computational expressions or mathematical functions meet the reasonable requirements of the input range of the computational expressions or mathematical functions, and can ensure that the computational expressions or mathematical functions can be calculated smoothly without violating physical laws or mathematical rules.

[0045] This invention applies graph optimization technology to ship replenishment route planning. By constructing a replenishment network graph, supply points and task points are abstracted as vertices of the graph, and potential ship navigation paths are abstracted as edges of the graph. The weights of the edges are determined by combining real-time sea state information. At the same time, a replenishment route optimization model with multiple constraints is constructed, which realizes the precise allocation of ships, material supply routes and material tasks, ensures a reasonable match between ship transportation capacity and material transportation requirements, and avoids situations of wasted or insufficient transportation capacity.

[0046] In the process of route planning, this invention fully integrates real-time sea state information and the ship's sea state adaptability. By setting sea state adaptability constraints, it ensures that the ship is only assigned to routes within its adaptability range, effectively reducing the impact of severe sea states on navigation safety, improving the safety of ship replenishment voyages, and reducing the probability of navigation accidents.

[0047] This invention sets time window constraints and determines the latest delivery time of supplies based on the urgency of the supply needs, ensuring that supplies can be delivered within the time allowed by the mission requirements. This effectively avoids situations where supply delays affect mission execution, improves the timeliness and effectiveness of supply replenishment, and guarantees the continuous progress of maritime missions.

[0048] A second aspect of the present invention discloses a graph-optimized ship replenishment route generation device, the device comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the graph-optimized ship resupply route generation method.

[0049] In a third aspect of this invention, a computer-readable storage medium is disclosed, the computer-readable storage medium storing computer instructions, which, when invoked by a computer, are used to execute the graph-optimized ship replenishment route generation method.

[0050] In a fourth aspect of this invention, an information data processing terminal is disclosed, which is used to implement the graph-optimized ship replenishment route generation method described above.

[0051] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for generating ship replenishment routes based on graph optimization, characterized in that, include: S1 collects a set of information on material demand, a set of information on material supply, and a set of information on ship transportation capacity. The set of material demand information includes information on each task point and corresponding material demand information; the material demand information includes the demand quantity, urgency of demand, and transportation requirements for each type of material; the task point information includes the location coordinates of the task point and the safe storage capacity index. The material supply information set includes information on each supply point and corresponding material supply information; the supply point information includes the location coordinates of the supply point and stable supply capacity indicators; the material supply information includes the inventory quantity and indicator completeness of each type of material; the transportation requirement information includes several transportation capacity indicator requirement values. The set of ship transport capacity information includes all transport capacity index values ​​and sea state adaptability values ​​for each ship; S2, perform optimization matching on the set of material demand information and the set of material supply information to obtain a set of material supply route information; S3, based on the material supply route information set and the real-time collected sea state information set, the ship transport capacity information set is planned and processed. By constructing and solving the replenishment route optimization model, the ship replenishment route information set is obtained, including: S321, based on the set of material supply route information, constructs a supply network diagram and a decision variable matrix. Abstract the supply task into a directed weighted graph. Vertex set It is the set of all supply points and task points included in the material supply route information set. For the collection of supply points; For task point set; edge set : Represents the potential path for a ship to move between vertices; the weight of each edge is determined by real-time sea state information and distance; a three-dimensional 0-1 decision variable matrix is ​​defined. This is used to represent the allocation relationship between ships, supply routes, and supply tasks; assuming... The total number of available ships. The total number of planned navigation mission batches; The total number of material categories; defined Decision variables in as follows: in, ; S322, Based on the Decision Variable Matrix Construct an objective function; the objective function The expression is: in, Assign matrix elements to the three dimensions defined above. To indicate the first ship to the first The transport capacity index values ​​for this type of material are derived from a collection of ship transport capacity information. Indicates the first The first of the material supply routes The required transport capacity indicators for this type of material are derived from the set of material demand information. , These are preset weighting coefficients used to balance the dimensions and priorities between capacity utilization and demand fulfillment; S323, Based on the supply network graph, constraints are constructed; the constraints include: (1) Task uniqueness constraint, which means that among all supply routes, a ship can only participate in the transportation of one type of material in one supply route. Its expression is: (2) Ship capacity and load constraints, used to indicate the constraints for each ship The total amount of supplies loaded on all its allocated supply routes cannot exceed its physical limits, as expressed by: in, , For the first The unit volume and weight of this type of material. , For the first The maximum cargo capacity and load capacity of the vessel; (3) Vessel sea state adaptability constraint, used to indicate that a vessel can only be assigned to a route permitted by its sea state adaptability value, assuming For ships Sea state adaptation value, For the supply route Given the sea state information, the expression for the ship's sea state adaptability constraint is: If the sea conditions along a supply route are too severe, exceeding the ship's tolerance threshold, then Forced to 0; (4) Time window constraint, meaning that materials must be delivered within the time allowed by the urgency of the need; assuming For the current time, For ships Implementing material supply routes Estimated sailing time: ， in, Indicates the first The latest delivery time of supplies to each task point; S324. Using the objective function and constraints, a supply route optimization model is constructed.

2. The method for generating ship replenishment routes based on graph optimization as described in claim 1, characterized in that, The optimization and matching process of the set of material demand information and the set of material supply information to obtain a set of material supply route information includes: S21, Perform material supply satisfaction screening on the set of material demand information and the set of material supply information to obtain a preliminary set of supply route information. S22, perform supply efficiency optimization processing on the preliminary supply route information set to obtain the material supply route information set.

3. The method for generating ship replenishment routes based on graph optimization as described in claim 2, characterized in that, The process of performing supply satisfaction screening on the set of material demand information and the set of material supply information to obtain a preliminary supply route information set includes: S211, Based on the material demand information set and the material supply information set, calculate the pre-selected supply route information to obtain the pre-selected supply route information set; S212, based on the set of material demand information and the set of material supply information, with the goal of ensuring sufficient material supply, the set of pre-selected supply route information is filtered to obtain a preliminary set of supply route information.

4. The method for generating ship replenishment routes based on graph optimization as described in claim 3, characterized in that, The calculation of pre-selected supply route information based on the set of material demand information and the set of material supply information, to obtain the set of pre-selected supply route information, includes: S2111, for each task point in the material demand information set, the supply point information in the material supply information set is filtered according to its corresponding material demand information to obtain the corresponding pre-selected supply route; the pre-selected supply route includes the task point and the corresponding supply point. S2112, using the pre-selected supply routes based on all task point information, construct a set of pre-selected supply routes; S2113, calculate the pre-selected supply route information for the pre-selected supply routes in the pre-selected supply route set to obtain a pre-selected supply route information set; the pre-selected supply route information set includes several pre-selected supply route information.

5. The method for generating ship replenishment routes based on graph optimization as described in claim 4, characterized in that, The expression for calculating the pre-selected supply route information is as follows: ， ， Where r is the distance of the pre-selected supply route, To ensure redundancy in the pre-selected supply routes, and These represent the safe storage capacity index of the task point and the stable supply capacity index of the supply point on the pre-selected supply route, respectively. (x1, y1) and (x2, y2) are the location coordinates of the task point and the supply point on the pre-selected supply route, respectively. and These are the bias factors for the preset safe storage capacity index and stable supply capacity index, respectively, and their values ​​are not 0; the distance and redundancy of the pre-selected supply route together constitute the pre-selected supply route information.

6. The method for generating ship replenishment routes based on graph optimization as described in claim 4, characterized in that, Based on the set of material demand information and the set of material supply information, and with the goal of ensuring sufficient material supply, the set of pre-selected supply route information is filtered to obtain a preliminary set of supply route information, including: S2121, Based on the aforementioned set of material demand information and set of material supply information, a material supply sufficiency screening model is constructed with the objective of material supply sufficiency. The expression for the material supply sufficiency screening model is as follows: , , , , , in, The selection factor for the i-th pre-selected supply route in the set of pre-selected supply route information is defined as follows: a value of 1 indicates that the pre-selected supply route is selected, and a value of 0 indicates that the pre-selected supply route is not selected. The value represents the sufficiency of material supply. The preset sufficiency threshold, , and These are the preset distance threshold, redundancy threshold, and total number of routes threshold, respectively. Q represents the total number of pre-selected supply routes, and K represents the total number of material categories. and Let be the inventory of the k-th type of material at the supply point of the i-th pre-selected supply route information and the demand for the k-th type of material at the task point, respectively. and These represent the distance and redundancy of the i-th pre-selected supply route information, respectively. S2122, using the pre-selected supply route information set as the solution set, the material supply adequacy screening model is solved to obtain a preliminary supply route information set; the preliminary supply route information set includes several feasible solutions; the feasible solution is a combination of selection factors that satisfy the material supply adequacy screening model; the combination of selection factors is a combination of selection factors corresponding to all pre-selected supply route information.

7. The method for generating ship replenishment routes based on graph optimization as described in claim 2, characterized in that, The process of optimizing the supply route information set to obtain a new material supply route information set includes: S221, Based on the aforementioned set of material supply information and set of material demand information, a supply efficiency optimization model is constructed; the expression of the supply efficiency optimization model is: ， , ， in, Let be the factor vector to be solved. , For the supply efficiency function, The selection factor for the j-th preliminary supply route in the preliminary supply route information set is defined as follows: a value of 1 indicates that the preliminary supply route is selected, and a value of 0 indicates that the preliminary supply route is not selected. The distance for the j-th initial supply route information. and These represent the urgency of demand for category k materials at the task point in the j-th preliminary supply route information and the completeness of indicators for category k materials at the supply point in the j-th preliminary supply route information, respectively. The total number of supply routes. , and The weighting factors are preset, all three are greater than 0, Q is the total number of pre-selected supply routes, and K is the total number of material categories; S222, Solve the supply efficiency optimization model to obtain the solution values ​​of the factor vector; S223, Select the corresponding preliminary supply route information from the preliminary supply route information set according to the solution value of the factor vector, and construct the material supply route information set.

8. A ship replenishment route generation device based on graph optimization, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the graph-optimized ship replenishment route generation method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, which, when invoked by a computer, are used to execute the graph-optimized ship resupply route generation method as described in any one of claims 1 to 7.

10. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the graph-optimized ship replenishment route generation method as described in any one of claims 1 to 7.

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