Research On Vehicle Routing Optimization Based On Genetic Ant Colony Algorithm

With the increase of the consumption level,basic food and clothing can no longer meet people's needs,more attention has been paid to the quality of life.In terms of diet,the fresh agricultural products are becoming more and more popular and the supply in the past has been unable to meet people's needs.How to ensure the quality of fresh agricultural products and distribution service become the focus of the route choice of fresh agricultural products distribution vehicles.The unique natural attributes of fresh agricultural products have caused the peculiarities of fresh agricultural products distribution methods,which mainly include several aspects: low temperature environment required,high transportation costs,individualized distribution,and scattered distribution points.To have a scientific optimal distribution route for fresh agricultural products,it is necessary to fully consider the constraints of the customer's time window,maintain the freshness of fresh products and meet consumers' time and product quality needs,but also optimize the distribution route and distribute the distribution reasonably Point,improve the fresh agricultural product distribution system,more attention should be paid to improve the efficiency of distribution and save the costs of distribution.The vehicle routing optimization problem of the AN Fresh Agricultural Products Company is taken as the research object in this paper.Describe the vehicle routing optimization problem of AN Fresh Agricultural Products Company and make corresponding assumptions,and establish three cost functions: fixed costs,transportation costs,and cooling costs,and customers that depend on the relationship between the vehicle delivery arrival time and the customer time window The satisfaction function builds a multi-objective optimization model with the lowest total cost value and the highest customer satisfaction.To solve the vehicle distribution route problem of AN Fresh Agricultural Products Company,three optimization algorithms:genetic ant colony hybrid algorithm(GAACO),genetic algorithm(GA),and ant colony algorithm(ACO)are set up respectively,and the three solution results are integrated Compare.Comprehensive analysis of the three algorithms found that the GAACO hybrid algorithm is the best solution among the three algorithms.For the same customer satisfaction,the company has the lowest expenditure,the least number of iterations,andthe fastest convergence.