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CN-122022656-A - Method for optimizing cargo load path of international freight agent

CN122022656ACN 122022656 ACN122022656 ACN 122022656ACN-122022656-A

Abstract

The invention relates to the technical field of international freight agents, in particular to an optimization method of a cargo loading path of an international freight agent, which comprises the steps of firstly collecting multi-source heterogeneous data and preprocessing, constructing a comprehensive database containing cargo characteristics, transport means, road condition policies and cost timeliness, establishing cargo loading priority and completing intelligent loading based on a hierarchical analysis-genetic hybrid algorithm, realizing accurate matching of weight, volume and characteristics and transport means cabin positions, then adopting an improved Dijkstra algorithm to conduct initial path planning by combining real-time dynamic data, dynamically adjusting the path through a rolling window iteration mechanism, and finally verifying the feasibility of a scheme through a cross-mode information interaction correction module, and generating an optimal loading path combination. The invention realizes the collaborative optimization of load and path, improves the dynamic adaptability and the resource utilization rate, reduces the transportation cost, shortens the transportation period, and is suitable for complex international freight scenes such as multi-type intermodal transportation, cross-border transportation and the like.

Inventors

  • XU SUQING

Assignees

  • 西安翻译学院

Dates

Publication Date
20260512
Application Date
20260203

Claims (10)

  1. 1. The method for optimizing the cargo allocation path of the international freight agent is characterized by comprising the following steps: The method comprises the steps of S1, data acquisition and preprocessing, namely acquiring cargo information, transport tool information, cross-border road condition information, policy and regulation information, cost aging information and environment information, denoising, standardizing and complementing the acquired data to construct a comprehensive database, wherein the cargo information comprises weight, volume, characteristics, aging requirements, fragile and perishable attributes and destinations, and the transport tool information comprises cabin capacity, load limitation, transport mode and operation and maintenance state; S2, generating an intelligent loading scheme, namely, based on a comprehensive database, adopting a hierarchical analysis-genetic hybrid algorithm, taking the lowest cost, the highest space utilization rate and the optimal time effect as targets, establishing a cargo loading priority, combining with the cabin parameters of a transport means, and completing the accurate loading of cargoes and transport means to generate an initial loading scheme; S3, dynamic path planning, namely dynamically generating an initial path by adopting an improved Dijkstra algorithm and combining real-time road conditions, port congestion conditions and flights/voyages based on an initial loading scheme, and updating dynamic data at preset time intervals through a rolling window iteration mechanism to iteratively adjust the path so as to avoid risk nodes; S4, scheme verification and optimization, namely comparing the situation that the allocation rationality, the path feasibility and the cost time reach the standard through a cross-modal information interaction correction module, and returning to S2 or S3 for re-optimization if the situation does not meet a preset threshold value until an optimal allocation path combination is generated; And S5, scheme execution and feedback, outputting an optimal scheme, guiding execution, and collecting actual data in the execution process to form a feedback closed loop for optimizing algorithm parameters.
  2. 2. The method for optimizing cargo allocation paths of an international freight agent according to claim 1, wherein in step S1, multi-source data acquisition is achieved through an Internet of things sensor, a cross-border transportation platform API interface, a customs supervision system and a third party weather platform, data preprocessing adopts a Lagrange interpolation method to complement missing values, and an outlier is removed through a standard difference method.
  3. 3. The method of optimizing a cargo allocation path of an international shipment agent according to claim 1, wherein in step S2, the priority evaluation index of the hierarchical analysis-genetic hybrid algorithm includes cargo aging weight, cargo value weight, characteristic adaptation weight, and space adaptation weight, the crossover probability of the genetic algorithm is set to 0.6-0.8, and the mutation probability is set to 0.01-0.03.
  4. 4. The method of optimizing a cargo allocation path of an international shipment agent according to claim 1, wherein in step S3, the path weight is corrected by introducing a risk cost factor including a congestion risk, a policy variation risk, and a weather risk by improving Dijkstra algorithm, and the rolling window iteration interval is set to 1-4 hours.
  5. 5. The method for optimizing cargo allocation paths of international freight agents according to claim 1, wherein in step S4, a mode of combining data of internet of things with manual verification is adopted by a cross-mode information interaction correction module, and the preset threshold comprises a space utilization rate of not less than 85%, a cost deviation of not more than 5% and an efficiency standard of not less than 95%.
  6. 6. The method of optimizing a cargo load path of an international organization for freight according to claim 1, wherein the adaptation of cargo characteristics in step S2 includes isolated loading of fragile objects and heavy objects, matching of perishable objects and refrigeration levels, and individual zoned loading of hazardous objects.
  7. 7. The method of optimizing a cargo allocation path of an international organization for freight according to claim 1, wherein in step S3, the dynamic data update contents include port berthing time variation, road construction information, customs clearance efficiency and extreme weather warning.
  8. 8. The method of optimizing a cargo allocation path of an international organization for freight according to claim 1, wherein in step S5, the feedback closed-loop data includes actual transportation cost, time consumption, rate of loss of cargo and number of path adjustments, and weight parameters for the iterative optimization algorithm.
  9. 9. The method for optimizing a cargo allocation path of an international organization for freight according to claim 1, wherein the transportation means comprises sea, air, land and multi-modal intermodal, and the optimal engagement scheme of the transfer nodes is automatically matched in a multi-modal intermodal scenario.
  10. 10. The method for optimizing cargo allocation paths of an international organization for freight according to claim 1, wherein in step S2, the initial allocation scheme adopts a three-dimensional bunk modeling technique to simulate cargo stacking state and avoid risk of gravity center offset.

Description

Method for optimizing cargo load path of international freight agent Technical Field The invention relates to the technical field of international freight agents, in particular to a method for optimizing a cargo allocation path of an international freight agent. Background With the continuous deepening of globalization trade, the international freight agency is used as a core link for connecting supply and demand parties and integrally transporting across the border, and the operation efficiency of the international freight agency directly influences the cost and timeliness of the international trade. Currently, international freight scenes are increasingly complex, various transportation modes such as sea transportation, air transportation and land transportation are involved, and multiple constraints such as various kinds of cargoes, various cross-border policies, uncertain road condition environments, and tense cabin resources are faced, and the traditional load and path planning method is difficult to meet the requirements of efficient operation of industries. The existing international freight agent cargo loading technology mostly takes space utilization rate or load balance of a single transport means as a core target, and lacks cooperative consideration of multidimensional factors such as cargo characteristics, time-lapse requirements, cargo value differences and the like. For example, part of the method only completes the loading through simple weight-volume proportion, does not carry out targeted partition on special cargoes such as fragile cargoes, perishable cargoes and dangerous cargoes, and is easy to cause the risk of cargo damage to be improved, meanwhile, the loading scheme and the path planning are mutually independent, the path planning is carried out after the loading is completed, the problem that the suitability of the loading scheme and the path nodes is poor often occurs, for example, after part of cargoes are loaded to a certain transport means, serious congestion or policy limitation exists on the path corresponding to the means, the re-loading is needed, and additional cost and time consumption are increased. In the aspect of path planning, in the prior art, a static path algorithm is mostly adopted, such as a traditional Dijkstra algorithm, an a-x algorithm and the like, and a path is generated only based on static data such as road conditions, port states and the like in the initial stage of planning, so that the real-time adaptation capability to dynamic factors is lacked. The international freight transportation has large cross-border span and long transportation period, and is easy to suffer from sudden conditions such as port congestion, flight delay, road construction, extreme weather, customs policy adjustment and the like, and the static path cannot be adjusted in time, so that the transportation aging delay is easy to be caused, and even contract default risks are caused. In addition, the partial path planning method does not fully integrate cross-border multi-link information, such as clearance efficiency of different countries, engagement capacity of transfer nodes and the like, so that the overall continuity of paths is poor, the transfer waiting time is too long, and the operation cost is further improved. Meanwhile, the prior art has insufficient data utilization capability, and the data of goods, transportation means, road conditions, policies and the like related to international freight presents multi-source heterogeneous characteristics, so that the traditional method is difficult to realize effective integration and preprocessing of the data, and the decision basis of loading and path planning is incomplete. For example, failure to acquire the real-time operational state of a vehicle in real time may load the cargo onto a tool at risk of failure, and failure to synchronize customs supervision policy changes in time may result in the cargo being retained in the clearance link. In addition, the existing method lacks an effective feedback closed-loop mechanism, and data in actual operation cannot be optimized by a back feeding algorithm, so that adaptability of a load path scheme is difficult to continuously improve. In addition, the problem of load path optimization in the current multi-mode intermodal scenario is particularly prominent. The multi-type intermodal transportation relates to the connection of various transportation tools, the existing method is difficult to integrate the coordination of a loading scheme and a transit path, the problems that goods are piled up at transit nodes, the connection of the transportation tools is unsmooth and the like often occur, and the transportation efficiency is greatly reduced. In summary, the existing international freight agent cargo loading path planning method has the defects of loading and path disconnection, poor dynamic adaptability, insufficient data utilization, insufficient multi-constraint cooperation and th