(405-2587-1-PB)SIMULATION-BASED OPTIMIZATION FOR RESOURCE ALLOCATION AT THIRD-PARTY LOGISTICS SYSTEMS

摘要

Allocating resource at third-party logistics systems differs significantly from traditional private logistics systems. The resources are considered commodities sold to customers of different types. Total yield suffers when over-allocate to lower-rate or price-sensitive customers; but the resource become “spoiled” when reserve too much for full-rate or time-sensitive customers that do not arrive as expected. Uncertain order characteristics make the optimization of such decisions very hard, if not impossible. In this paper we proposed a simulation-based optimization to address related issues. A genetic algorithm based optimization module is developed to generate/search good solutions; and a discrete-event simulation model is created to evaluate the solutions generated. The two modules are integrated to work in evolutionary cycles to achieve the optimization. The study also compared GA/Simulation model with more traditional approach such as response surface methodology via designed experiments. The models were validated through experimental analysis.