Research Of Intelligent Logistics Route Optimization Problem

In recent years,intelligent logistics has become a hot topic.With the rapid development of China's economy as a whole and the change of national consumption pattern in the Internet era,significantly increased demand for logistics industry,modern logistics technology is urgent to more convenient and intelligent direction.In order to meet the ever-expanding demand,and effectively control the growing logistics cost,intelligent logistics emerges.Among them,logistics distribution is the most important link in the intelligent logistics system,which plays a supporting role in the logistics operation.However,it also occupies a considerable proportion in the cost composition of intelligent logistics,and how to reduce the logistics cost,improve the intelligent logistics system,more and more attention.Therefore,route optimization,as an important research and solution of logistics distribution,has become the focus of intelligent logistics research.This thesis focuses on the hot question of route optimization in intelligent logistics,and has carried out relevant researches.This thesis introduces the current research status of logistics distribution route optimization problems and the development and research of relevant algorithms.Then,a detailed description of the logistics distribution problem was given,and the common mathematical models were enumerated,at the same time,this thesis introduces the basic algorithm about the logistics distribution route optimization problem and classification.In this thesis,the principle of immune algorithm and particle swarm algorithm is studied in detail,and the advantages and disadvantages of the two algorithms are summarized.A new algorithm named IA-PSO is proposed based on the advantages of global optimization ability,positive feedback and immune algorithm global convergence and antibody diversity.The immune processing mechanism of the IA is involved into original PSO,it enables the particle swarm algorithm to get rid of the local optimal solution in a timely manner,and searches for other locations in the solution space,until the global optimal solution was found.The introduction of this mechanism effectively improves the convergence speed and accuracy of the algorithm at the later stage of operation.In this thesis,we set up an integrated logistics distribution problem model with time window and a multi-distribution center logistics distribution problem model,and determine the constraint conditions of the model.The IA-PSO is applied to solve the optimal route of the problem model,and we using computer programming to implement algorithm.Through the experiment,the differences between the two models are compared between the immune particle swarm algorithm and the other algorithms.Finally,the feasibility,stability and efficiency of the immune particle swarm algorithm in solving different types of route optimization problems are proved.