| With the integration of online and offline channels for home appliance retailing,Jingdong home appliance store has become an important driving force.At the same time,the rural market scale is exploding.Under the fierce competition environment,Jingdong home appliance store need to continuously improve the county-town retail and logistics system,thereby improving service efficiency,reducing overall operating costs,improving Jingdong's economic and social benefits,and it's own competitiveness.Therefore,the research on the county-town logistics network optimization of Jingdong home appliance store has important theoretical and practical significance.The paper analyzes the overall development of county-town home appliance logistics,as well as the layout,operation and logistics mode of Jingdong county-town appliance store.Identify the research scene and determine two research objects including the site selection of county-level Jingdong home appliance store and the optimization of county-town distribution routes based on above analysis.The model is constructed'by setting principles,assumptions,parameters,objective functions and constraints on the two problems.Use LINGO to solve the location model of county stores,and output the most preferred address plan and the corresponding cost value.Solve the distribution path optimization model,and output the iterative convergence trend graph,the optimal distribution path and the corresponding cost value by using MATLAB.In coding sorting,add integer encoding and search sorting to complete the encoding.Then combine roulette with fitness ordering.Finally,cross partial gene segment by pre-removal and eliminating repeat.Inoder to accelerate the convergence speed and find the optimal solution.Select a county of Xi'an in Shaanxi Province as an example.Design parameters considering the actual situation to solve the location model of the county store and the optimization solution of county-town distribution path.Find the influence law of each parameter on the objective function and complete the sensitivity analysis.At the same time,the feasibility and effectiveness of the improved algorithm are verified by comparing the improved genetic algorithm with the traditional genetic algorithm for the same parameters.The summary and research prospects are the last item of the paper.In this thesis,there are 34 figures,28 tables,and 83 references. |
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