关键词: 物流, 越库, 仿真, 序贯分支, 响应面元模型, Kriging元模型

Abstract: Automobile and logistics are the two critical restructuring and invigorating industries in China. In the context of assembly plant capacity expansion, the optimization design of Third-Party Logistics Milk-Run Cross-Docking (TPL-MRCD) with the average process time of parts as performance index was researched deeply, and the simulation model which satisfied the actual logistics operation demand was established. Owing to existing of many simulation input factors, the key factors were screened by Sequential Bifurcation, and the research procedures of Response Surface Methodology (RSM) and Kriging meta-model was built for key factors. Thus the difficult optimization problem caused by multi-dimensional factors was solved.The simulation experiment calculated by investigation data showed that the logistics performance could reach an ideal level through optimal allocation of key factors; the prediction result of Kriging meta-model was better than optimum performance value of response surface. The proposed model and method could provide reliable solution for formulating TPL improve plan after expanding capacity and guide to solve the optimization issue of complex simulated system.

Key words: logistics, cross-docking, simulation, sequential bifurcation, response surface meta-model, Kriging meta-model