Solving The Problem Of Logistics Distribution Center Location Based On Improved Gravitational Search Algorithm

Logistics distribution centers play an important role in the entire supply chain network,connecting suppliers upstream of the supply chain with downstream retailers(or distributors)into an organic system.Proper distribution center location solutions can also reduce delivery efficiency,enhance competition levels and develop potential while reducing their own operating costs.In addition,the location scheme has a significant impact on the logistics costs of suppliers,distributors and retailers who have business dealings with the distribution center.Henan Province,the implementation of the implementation of Luoyang,Shangqiu,Nanyang,Xinyang,Anyang,Puyang,Sanmenxia 7 logistics node city construction program,built with 15 regional distribution and urban logistics and distribution cen.Therefore,the study of the distribution center location can promote the development of the entire logistics network.Gravitational search algorithm is a new intelligent optimization algorithm proposed by E.Rashedi inspired by Newton's law of universal gravitation and the second law of kinematics.The algorithm is based on the law of gravitation and the interaction between particles,that each particle in the space is subjected to the gravitational action of other particles,and the particles in the space are moving in the direction of the particles with the largest gravitational force.As the particles continue to move,the particles eventually converge near the mass of the particles,and the position of the particles with the highest mass is the optimal solution of the problem.It is found that the optimization precision and convergence rate of gravitational search algorithm are better than genetic algorithm and particle swarm optimization algorithm in the standard test function optimization experiment.The purpose of this paper is to apply the improved gravitational search algorithm to three different logistics distribution center location problems,and compare the results with the standard gravitational search algorithm and particle swarm optimization algorithm,The following work has been carried out for this purpose:(1)Firstly,it introduces the paper's background and significance,and the research status of logistics and distribution center in China and abroad.This paper introduces the definition,type and function of logistics distribution center and the basic principles and methods of logistics and distribution center selection.For the next research content to do the theoretical basis of bedding.(2)In this paper,we introduce the concept of distance threshold to measure the distance between individual particles and contemporary optimal particles.Each particle independently adjusts the gravitational force independently,and realizes the algorithm global search ability and local search for the gravitational search algorithm.The dynamic balance of the ability improve the convergence rate of the algorithm.Aiming at the problem of premature convergence of the algorithm,a mutation strategy based on the degree of particle aggregation is proposed.The strategy avoids the problem of early convergence of the algorithm by the value of the parameter.Finally,the experimental results show that the improved gravitational search algorithm can improve the convergence speed and convergence precision of the algorithm.(3)The improved gravitational search algorithm is applied to solve the problem of single facility,continuous location problem,multi-facility,discrete location problem,multi-facility,continuous and constrained location problem.The improved gravitational search algorithm MATLAB program is written and the results of the solution are compared with the results of the standard gravity search algorithm and the results of the particle swarm algorithm.The feasibility of the improved gravitational search algorithm to solve the logistics distribution center location is verified.