关键词: 部分转运, 随机模糊, 粒子群优化, 模拟退火算法, 时间约束, 库容空间限制, 就近原则

Abstract: To solve the multi-spot inventory sharing problem in an emergency system, emergency transportation strategy was studied in a system with random fuzzy demand in this paper through a multi-product and three-echelon emergency supply system. When the stockout happened, the nearest emergency lateral transshipment principle and partial inventory sharing strategy among the spots were permitted to satisfy the demand, and the model for the total cost expectation of random fuzzy demand was developed according to it, taking account of the service time constraints and the spots' storage space limitation. An advanced computing method combining Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithm, called PSO-SA algorithm, was proposed to calculate the model, and the effects on the partial transshipment with the variation of the transshipment trigger inventory level, the per-item transshipment time and the inventory storage space were analyzed through a numerical example. The availability of the proposed algorithm and the model applicability were verified at last.

Key words: partial transshipment, random fuzzy, Particle Swarm Optimization (PSO), Simulated Annealing (SA) algorithm, time constraint, storage space limitation, proximity principle