Abstract

This paper discusses the problem of the automobile sparepart logistics warehouse network strategy, a quite important problem inlogistics. On the basis of the integration of quantitative technology andqualitative technology, a mathematic model and algorithm of automobile spare partlogistics network optimization are presented. In the quantitative analysis partwe propose a novel hybrid approach through crossing over the PSO and GA, calledhybrid PSO-GA based algorithm. Among the mixed algorithm, GA is embedded tosolve the difficulties of updating the particles in the binary code system; theroulette algorithm is embedded to eliminate worse particles; SA is embed tocontrol convergence of particles. Then in the qualitative part, we propose aselection model along with the AHP methodology that project selection would beeasier and more accurate than before. In the end we apply the above approach inan automobile spare part logistics company. Computational simulation is carriedout to evaluate the performance of the algorithm and the results show that thisapproach can indeed find effective solutions for the automobile spare part logisticsoptimization problem. 

1.  Introduction

Low-cost hasbecome a major consideration for car manufacturers. A quickly increasing carpopulation and demand enlarge the market for service and spare-parts day byday. For instance, in European, American and Japanese auto market, the sales ofspare parts is nearly one-half of the auto sales^[1].Meantime, theinventory system of automobile spare is of characters such as categorynumerous, demand and lead time highly uncertain etc. Besides, phenomenon of “Trade-Off”also exists between huge inventory carrying costs and low service level forcustomers. Present logistics literatures such as E.G. and X. Kuo (2007)^[2]putservice in the same position as cost.