Research On Vehicle Scheduling Problem Of Distribution Center Based On Improved Particle Swarm Optimization

In recent years,with the development of e-commerce,the deepening of freight reform and the rapid transformation of the railway to the modern logistics enterprises,the logistics industry ushered in its another great development,the status of logistics distribution in the economic activities become more prominent as well.However,the rapid development would bring new challenges,as an important issue in logistics distribution-vehicle scheduling problem become the focus of scholars again.The vehicle scheduling problem has developed for decades,but with the continuous development of society,there are still some new problems with distinctive characteristics of the times constantly,especially to support the development of logistics,customer satisfaction in logistics distribution becomes more important and the influence on the enterprises too.Distribution is a kind of nature of the service industry,so the vehicle scheduling optimization problems is not only to reduce the cost of distribution enterprises,but also to improve the efficiency of service and enhance customer satisfaction index,and then improve the competition of distribution enterprises,enabling them to get a long-term development in the fierce competition.Based on the existing literature and research results,this paper establishes a model of vehicle optimal scheduling problem for customer satisfaction,the use of particle swarm algorithm and improved particle swarm algorithm respectively to solve the model examples and verify the effectiveness of the algorithm.Details as follows:(1)In terms of model building.In order to get a better customer satisfaction assessment evaluate and make the model more close to reality,In this paper,introduced the trapezoidal fuzzy time function,evaluated the customer satisfaction by the customer's expected service time and the allowable service time two factors,adding the cost and time factors at the same time,finally,established a multi-objective model which satisfies the maximum customer satisfaction and the minimum time and cost.(2)In algorithm respect.Firstly,studied the algorithm of vehicle scheduling problem in detail,and illustrated the advantages and disadvantages of different algorithms by comparing and analyzing them.Then,introduced bacteria swarm algorithm in the replication and migration operator to improve it aiming at the limitation of the standard particle swarm algorithm,used the standard test functions to verify the algorithm.It can be concluded that the improved particle swarm algorithm is better than the standard particle swarm algorithm which has much stronger search ability and the ability to jump out local optimal.At last,in order to better use the particle swarm optimization algorithm,the coding method and evolution mode of the particle are improved,and the choice of the weight scheme is discussed,through the analysis and comparison of the solution of the example,proved the Validity of Algorithm of the improved particle swarm in Solving Vehicle Scheduling Problem finally.