Joint Optimization Of AGV Filling And Routing Problem For Automotive R&D Materials

After a period of rapid global market growth in the automotive industry.The research and development cycle,testing cycle and trial-producing cycle of new models and components are shorter,at the same time,the pace of technological upgrading is faster.In order to adapt to the market characteristics,automotive research and development center build an integrated,intelligent and lean logistics service system to improve trial production capacity and operational efficiency.Considering that R&D(research and development)materials are used in R&D,testing and trial-producing of new products,which have the characteristics of new functions,many series and small batches,and a challenge to realize the AGV lean distribution target in the park is proposed.The strategic decision of lean supply for R&D materials based on AGV involves two parts: AGV material loading and AGV route planning.Considering the actual situation of R&D center's split delivery and the target requirements of distribution timeliness,this paper focuses on the joint optimization of vehicle filling problem and split delivery vehicle routing problem with soft time window.Based on the classic vehicle filling problem and split delivery vehicle planning problem,this paper discusses the joint optimization of outside AGV filling and routing problem for R&D material demand characteristics in the park of automotive R&D center.Firstly,this paper describes the content of R&D material management.Through the k-means clustering analysis on volume and weight,the standardization of R&D material packing can be realized.Secondly,combined with the actual situation of the automobile R&D center,the joint optimization of AGV filling and routing problem is defined.The soft time window and split delivery strategy are introduced to construct the joint optimization model of AGV filling and routing based on the minimum total distribution cost as the objective function,and the basic assumptions and constraints are given.Finally,select and design genetic algorithm to obtain the solution.Based on the orthogonal test method,the parameters of the algorithm are optimized,and the results obtained by the genetic algorithm are better.The results show that the k-means clustering analysis of volume and weight can be used to realize the packing standardization of R&D material,which is theoretically feasible.The joint optimization model of AGV filling and routing problem with soft time window and its algorithm are effective.