Research On Location–Allocation Of Cloud Logistics Based On Immune Optimization Algorithm

With the continuous development of information technology,logistics theory and applied research,the pace of construction of logistics and distribution center is accelerating,the location and distribution of distribution center has become a key problem to be solved urgently in the process of logistics development.In the traditional logistics location-allocation problem,the allocation relationship between distribution center and demand point is "one to one" or "one to many",It shows that the logistics resources of the distribution center are operated independently,and can not cooperate with the logistics tasks of the same demand point in many distribution centers.This led to the waste of logistics resources,logistics costs increase.This requires us to use new thinking to solve these problems.Because the cloud logistics platform can integrate and dispatch the logistics resources,on this basis,this paper studies the location-allocation model of cloud logistics in order to achieve the correct site selection and coordinated distribution.At the beginning of this article,the background and significance of the research,site selection and allocation,as well as the research status of cloud logistics at home and abroad are expounded.Then we describe the traditional theory of location problem,cloud logistics and immune algorithm.It shows the coverage radius and state of the location-allocation model under the traditional logistics model and the cloud logistics model,and gives the optimal location scheme in different situations.After a series of analysis and reflection,we design a collection distribution and maximum coverage location-distribution model under the cloud logistics.The number of cloud stations and the service radius are unknown,and the demand of the demand point is completely covered.However,The coverage model is to cover as many needs as possible given the radius of service and the number of stations already known.Finally,this paper expatiates on the demand and development status of auto parts and the current situation of supply chain logistics.It is of great significance to study the location and allocation of auto parts distribution center under cloud background.The paper uses the matlab tool and the immune optimization algorithm to analyze and solve the auto parts data of the above two models,and gets the following simulation results: the convergence curve of the fitness function of location-allocation model in cloud logistics model;Model location and distribution results;site selection for the minimum cost of building a station,the demand distribution results to the lowest logistics operation cost;According to the distribution results found in the cloud logistics model,distribution centers and demand points of service distribution ratio The relationship is a certain value of 0-1,multiple distribution centers can be a number of demand points for coordinated distribution,in line with the "cloud" logistics resources under the logistics resources should be integrated and collaborative together for the demand point service purposes;the traditional mode Its assigned value can only be 0 or 1,unable to cooperate.Therefore,the final conclusion is that the cloud logistics model has more advantages than the traditional model.