Distribution Technology Research On Chain Enterprise Logistics Distribution Center

In this dissertation, several aspects of chain store running and logistics distribution center such as the concept, the features, the functions and the operation process are introduced at first. Some scheduling optimization problems of logistics distribution center such as order-picking for multi-level carousel with two server order-picking for fixed shelves and vehicle scheduling for distribution traffic are indicated.The order-picking route optimization for carousel and fixed shelves can largely improve the efficiency of the automated warehouse. The multi-level carousel is the latest development in the automated warehouse. It is specifically applied to store small parts. The literatures on order-picking problem of the carousel were mainly concentrated on the single server, few papers were devoted to the case of two servers. In this paper, based on two-level genetic algorithm, an improved approach is proposed to order-picking optimization of multi-level carousel system with two servers. The heuristic method was first used in single carousel optimization, and then genetic algorithm was used in entirety optimization. The results of the computer simulation show that it can deeply shorten the time of sorting out.Fixed shelves have large proportion in cubic warehouse and many goods store in it especially large goods. A new approach is proposed in this paper for extensive order-picking optimization of fixed shelves system. The whole indenture is firstly separated into some sub-indenture, and genetic algorithm was used to optimize every sub-indenture, then heuristic method was used to connect optimized sub-indenture. The results of numerical simulations show the validity of this approach.Distribution traffic is the last program for distribution center sending the goods out. The efficiency of traffic will affect the quality of distribution. The route optimization for traffic can reduce traffic cost and advance traffic efficiency. For this purpose, an improved genetic algorithm is given to optimize the distribution route for different traffic task. The numericalresults of different size show the validity of improved algorithm comparing with simple genetic algorithm.