Research On Logistics Vehicle Routing Problem Based On Heuristic Optimization Algorithm

In the 21 st century,China's GDP has risen rapidly,and many industries have flourished.Especially the logistics industry that is booming today is the basic pillar industry of China's economic development.However,because the level of logistics and transportation is limited by the high logistics and transportation costs,Greatly hinder the development of many domestic logistics companies.This makes it an important issue for academics and industry to effectively improve the level of logistics and transportation and save logistics and transportation costs.Based on the early operation mode of the logistics industry,the academic community has proposed the vehicle routing problem.For this reason,domestic and foreign scholars have done a lot of research and achieved many good research results,but with the development of science and technology,today's logistics industry encounters The problem of vehicle routing is also more complicated and variable,which leads to more problemsmulti--constrained vehicle routing problem,multi-center vehicle routing problem and multi-objective multi-constrained multi-center vehicle routing problem.There are not many studies,especially the research on multi-objective multi-constrained multi-center vehicle routing problems.Based on this paper,the research background of the vehicle routing problem and its extension problem is firstly presented.The research results of the current vehicle routing problem and its extension problem are analyzed.The basic vehicle path is separately analyzed by referring to domestic and foreign literature review and research results.The problem,multi-constrained vehicle routing problem and multi-objective multi-constrained central vehicle routing problem were analyzed in detail and the corresponding mathematical model was established.Then based on these established models,the method principle of heuristic optimization algorithm is deeply studied,and the heuristic optimization algorithms which are applied to basic vehicle routing problems and multi-constrained vehicle routing problems at home and abroad are analyzed and improved.Two improved heuristic optimization algorithms are proposed to solve the corresponding vehicle routing problem more effectively.Then,for the more realistic and complex multi-objective multi-constrained multi-center vehicle routing problem,the idea of hybrid optimization is used to innovate the particle swarm algorithm,genetic algorithm and ant colony algorithm in stages,and an ant colony is proposed.The algorithm-based hybrid multi-objective ant colony optimization algorithm solves the multi-objective multi-constrained multi-center vehicle routing problem.At the same time,this thesis carries out detailed experiments on the proposed algorithm,and uses the proposed algorithm and current domestic and foreign logistics enterprises to apply the best taboo search algorithm andvariable neighborhood search algorithm in vehicle routing problem and its extension problem.The largest and smallest ant colony algorithm was tested in an internationally recognized Solomon benchmark data set.The experimental results show that the two improved heuristic optimization algorithms can solve the corresponding vehicle routing problem more effectively,and the proposed hybrid multi-objective ant colony optimization algorithm is also very suitable for solving multi-objective multi-constrained multi-center vehicle routing problem.Finally,the hybrid multi-objective ant colony optimization algorithm proposed in this paper is applied to practice,and a multi-constrained multi-center logistics planning system is designed based on software engineering to solve complex multi-objective multi-constraints for domestic and foreign logistics companies.The central vehicle routing problem provides an effective reference and reference.