Research On Vehicle Routing Problem With Soft Time Window Based On Hybrid Intelligent Optimization Algorithms

In recent years,China's logistics service industry has developed rapidly.Vehicle routing problem is particularly critical.How to reduce the total cost of logistics has become our focus.Therefore,optimizing vehicle routing,reducing total transportation costs and making logistics services more environmentally friendly have become the inevitable trend of future development.In the vehicle routing optimization problem,the vehicle routing optimization problem with soft time windows is also a representative problem.It can be extended to the vehicle routing optimization problem with hard time windows,and can also be transformed into the basic vehicle routing problem.The vehicle routing optimization problem with soft time windows is also a complex NP-hard problem.Therefore,based on this practical significance,this paper studies the vehicle routing optimization problem with soft time windows.It is very meaningful to study the algorithm of vehicle routing optimization with soft time windows.The main contents of this paper are as follows:(1)Five key elements of vehicle routing problem are studied,and the extension problems of various vehicle routing problems are analyzed,including dynamic vehicle routing problem,Multi-depot and multi-vehicle vehicle routing problem,open vehicle routing problem,pick-up and delivery vehicle routing problem and periodic vehicle routing problem.This paper studies the vehicle routing problem with time windows,introduces the vehicle routing problem with time windows from different angles,and analyses the advantages and disadvantages of various current algorithms to solve the vehicle routing problem with soft time windows,which makes adequate preparations for the research of vehicle routing problem with soft time windows.(2)We have established the mathematical model.This paper discusses the hypothesis of the vehicle routing problem with soft time windows,such as distribution stations,customer nodes,vehicle transportation road network,ultimate goal and vehicle.The objective function is designed,and the problem constraints of the vehicle routing problem with soft time windows are defined.This provides a theoretical basis for the experiment of the vehicle routing problem with soft time windows.(3)An improved brainstorming ant colony optimization algorithm is proposed to solve the vehicle routing problem with soft time windows.By analyzing the reasons why ant colony algorithm is easy to fall into local optimal solution,an improved brainstormingoptimization algorithm is proposed to update the problem solution obtained by ant colony after one iteration search.The improved brainstorming optimization algorithm enriches the solution of the problem in each iteration of the traditional ant colony algorithm,so that the pheromone distribution is diversified,and the ant can jump out of the local optimal solution in the next iteration.The experimental results show that the proposed improved brainstorming ant colony optimization algorithm can effectively solve the vehicle routing problem with soft time windows.(4)To solve the vehicle routing problem with soft time windows in decentralized and hybrid client nodes,this paper proposes a head-tail bat ant colony algorithm.The characteristics of vehicle routing problem with soft time windows in decentralized and hybrid customer nodes are analyzed.An improved bat random vibration method is proposed to update pheromones in ant colony algorithm,which improves the pheromone updating process.The method of updating the solution set from the beginning to the end is proposed to enrich the diversity of solutions and make the algorithm have better search ability.The experimental results show that the head-tail bat ant colony algorithm can reduce the total transportation cost at a faster convergence rate.