Cargo optimization distribution method and system based on ant colony algorithm

Abstract

The invention relates to the technical field of target optimization, and discloses an ant colony algorithm-based cargo optimal distribution method. The method comprises the following steps: obtaining cargo distribution information, and carrying out coding representation on the cargo distribution information to obtain a cargo distribution information coding result; establishing a multi-objective function of cargo distribution, and initializing ant colony algorithm parameters; placing a plurality of ants at the path node positions in the cargo distribution information coding result, and enabling the ants to select the node positions where the ants need to walk in the next step according to the volatilization factors and the heuristic factors until all nodes are traversed, and ending the algorithm of this round; after each round of algorithm iteration, updating the pheromones of the algorithm until the maximum number of iterations is reached, selecting the path with the minimum multi-objective function value from all the paths as a cargo distribution optimal solution of the multi-objective function, and outputting an optimal distribution path result of cargo distribution. The invention further provides a cargo optimal distribution system based on the ant colony algorithm. According to the invention, optimized cargo distribution based on the ant colony algorithm is realized.

Description

technical field [0001] The present invention relates to the technical field of target optimization, in particular to an ant colony algorithm-based cargo optimization distribution method and system. Background technique [0002] With the rapid development of domestic e-commerce and express delivery industry, the demand for online shopping and off-site procurement is growing rapidly, the business volume of express delivery companies is increasing day by day, and people have higher requirements for logistics and distribution. At present, the cost of logistics and transportation in my country is relatively high at this stage, and the timeliness requirements for transporting goods are also high. How to better improve the delivery efficiency of goods and reduce the cost of logistics and transportation is an urgent problem to be dealt with now. [0003] The heuristic algorithm can be used to solve the optimal feasible solution, which can be more suitable for dealing with a wide ran...

AI Technical Summary

Problems solved by technology

The ant colony algorithm is a traditional heuristic algorithm, which is abstracted from the action of finding the path in the process of finding food by ants. It is an algorithm that finds a better path and has a certain degree of randomness. However, the traditional ant colony algorithm has a long search time. , easy to fall into partial optimal solution and iterative redundancy

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