Research On The Choice Of Intelligent Matching Methods For Cloud Logistics In Automobile Manufacturing Enterprises

Since the 21 st century,the global automotive industry has developed rapidly.Each car consists of an average of 10,000 parts.From parts procurement,to the final delivery of the vehicle to the 4S shop,all involved in logistics.At present,the logistics mode of the automobile manufacturing industry is still in the procurement mode.Suppliers and manufacturing companies have reached an agreement to purchase on demand.This method will cause serious waste of resources.With the increase in demand and supply,the traditional on-demand ordering method can no longer meet the development needs of the automotive industry.In order to improve production flexibility and promote the development of the automobile manufacturing industry,it is particularly important to adopt intelligent matching technology.Firstly,the paper collects and reviews the research on cloud logistics intelligent matching method.By comparing the research content,research methods and research status,the paper summarizes it is necessary to select the intelligent matching method to achieve the development goal of the automobile manufacturing industry.Secondly,the paper summarizes the types and structure types of cloud logistics resources,through the sorting of cloud logistics resources of automobile manufacturing enterprises.Furthermore,the paper constructes the overall framework for implementing cloud logistics services.and clarifies the various aspects of logistics demand in the manufacturing process of automobile manufacturing from the perspective of automobile manufacturing,and the cloud logistics resources of automobile manufacturing industry are described as computer resources.Then,the current methods of cloud logistics resource discovery and three intelligent matching methods are analyzed in details,they are based on heuristic algorithm,module-based and process-based.Considering both the performance of expert intelligent matching methods and enterprise expectations,the paper selectes the most important indicators for the automobile manufacturing industry and summarize the five most important factors affecting the development of cloud logistics in automobile manufacturing by rooted theory.According different ability of different methods of different indicators,the advantages and disadvantages performance of the three methods is detailed comparisoned.Considering the current situation and development prospects of the automobile manufacturing industry,the paper combines the characteristics of different intelligent matching methods,and builds a prospect value model to help enterprises select the intelligent matching methods suitable for their own development.The paper provides theoretical reference and certain guidance for the development of cloud logistics in automobile manufacturing industry to select intelligent matching methods for achieving flexible,high-quality,efficient,punctual,low-cost,clean target tasks.