Research On Resource Sharing Tribution Path Optimization

With the development of economy,the modern logistics industry is developing towards the direction of scale and integration,and the emphasis of logistics enterprises on "reducing efficiency" is also increasing day by day.Based on the integration of logistics resources and the sharing of warehouse resources,this paper will optimize the resource-sharing logistics distribution network.The research of this paper is divided into two parts,the first part is to study the warehouse resource sharing logistics distribution network,its corresponding mathematical model is the classical Multi-depot Vehicle Routing Problem(MDVRP),and the second part is on the basis of the first part of the Warehouse resource sharing(multi-depot)research,Further realize the sharing of distribution vehicle resources(open)and customer resource sharing(demand can be split),and establish the corresponding Multi-depot Open Split Demand Vehicle Routing Problem(MDOSDVRP)model.In the study of MDVRP,the characteristics of MDVRP model are analyzed first,and after the analysis of different solving strategies,the"whole method" is used as the solution strategy of this paper.Then a hybrid genetic algorithm is designed for this model,which exists when the classical genetic algorithm is solved in the solution of MDVRP:(1)The chromosome length caused by codec is not fixed,the calculation efficiency is low,easy to produce the non-feasible solution,and(2)The calculation efficiency of the parent genetic operator is low during the disturbance process.(3)It is difficult to balance the relationship between elite ratio and population diversity,search depth and search breadth in populations in different evolutionary periods.The distribution network information is expressed separately in the compilation and decoding method,which improves the calculation efficiency,and the control parameters of balancing elite ratio and population diversity are introduced in the selection operation.In addition,an adaptive search scope strategy is introduced to effectively balance the relationship between search depth and search breadth.Finally,in the solution and analysis of the example,the comparison experiments of different genetic operators and solving strategies are carried out respectively,and then a small example is used to verify the validity of the algorithm,and the efficiency of the algorithm is tested by a standard example.In the study of MDOSDVRP,the characteristics of the MDOSDVRP model are analyzed first,and the diversity of the initial population is guaranteed by using the internal randomness of the chaotic optimization algorithm on the basis of the classical genetic algorithm,and the probabilistic acceptance and deterioration mechanism of the simulated annealing algorithm is introduced to enhance the local search ability.;At the same time,an improved search Neighborhood Size Reduction Scheme(NSRS)is introduced to limit the search radius and improve the search quality.In the solution and analysis of the example,a small example is used to verify the validity of the algorithm,and then the efficiency of the algorithm is tested by two sets of standard examples,and then the performance of the algorithm is compared and experimented,on the basis of which,finally,by constructing an example to compare MDVRP,The distribution cost of three kinds of resource-sharing logistics distribution networks in MDSDVRP and MDOSDVRP,and illustrates the advantages of resource-sharing logistics distribution network.The research in this paper is suitable for resource-sharing distribution network,which can further reduce the distribution cost of logistics enterprises and provide a theoretical solution for multi-region joint distribution of logistics enterprises.