| With the rapid development of Internet technology,the global economy is further deeply integrated,the flow of production factors of international trade activities is accelerated,the global trade infrastructure is further improved,and the global cross-border e-commerce has developed rapidly in the world market.At the same time,China’s cross-border e-commerce seized the opportunity of The Times,actively layout the global market under the premise of policy support and science and technology support,the overall scale of China’s cross-border e-commerce continues to expand and show huge potential development space,cross-border logistics mode has been diversified development,the overseas warehouse as the representative of the new cross-border logistics mode emerged.Since the novel coronavirus epidemic swept the world,cross-border trade has been continuously affected,and traditional cross-border e-commerce logistics has been greatly impacted after encountering bottlenecks.In order to solve the problems of poor timeliness,high service cost and low customer satisfaction in traditional cross-border e-commerce logistics,realize the localization of cross-border trade,increase the share of enterprises in overseas markets and improve consumers’ shopping experience,Chinese cross-border e-commerce enterprises have set up overseas warehouses in overseas markets.However,at present,the construction of overseas warehouse in China’s cross-border e-commerce industry is still in the development stage.How to select the address of overseas warehouse scientifically and reasonably and give full play to the function of overseas warehouse with maximum validity is the primary problem for cross-border e-commerce enterprises to solve when choosing overseas warehouse mode.First of all,this thesis explains the relevant theoretical basis of overseas warehouse,and compares and analyzes the general algorithm of overseas warehouse location,expounds the advantages of particle swarm optimization algorithm and the reason of using particle swarm optimization algorithm in this thesis.Secondly,this thesis analyzes the factors affecting the location of offshore warehouses of China’s cross-border e-commerce from macro and micro perspectives.Thirdly,based on the dual objectives of minimum total cost and highest customer satisfaction,the mathematical model of dual-objective particle swarm optimization algorithm is established in this thesis.Finally,based on relevant data,this thesis considers the supply point,overseas warehouse and demand point,constructs corresponding examples,and uses MATLAB software for analysis,verifies the effectiveness of biobjective particle swarm optimization algorithm for overseas warehouse location,and further optimizes the methods and strategies in the study of overseas warehouse location.Through theoretical research and numerical example analysis,this thesis draws the following conclusions: First,as the key node of cross-border e-commerce logistics system,overseas warehouse can effectively solve some problems existing in traditional cross-border logistics;Second,the location of overseas warehouses should follow the principle of combining macro and micro factors,fully consider the factors affecting the development of overseas warehouses,and make strategic planning for the long-term development of overseas warehouses in the future.Thirdly,the particle swarm optimization algorithm can provide reasonable suggestions for the location of overseas warehouses.Cross-border e-commerce enterprises can choose the best overseas warehouse address according to their own development needs. |