关键词: 供应链管理, 合补充问题, 模糊机会约束规划, 三角模糊数, 遗传算法

Abstract: Supply chain inventory optimization problem under uncertain environment is concerned. Fuzzy chance constrained programming model for multi-item joint replenishment is thus proposed, which can take into account fuzzy demand quantity, as well as the constrained conditions are not satisfied to a certain degree. Demand quantity is a triangular fuzzy number, combined with the possibility of credibility measure theory. The objective function is to minimize the expected discounted cost of ordering and inventories in the supply chain. Genetic Algorithm（GA） is used to solve the obtained optimality conditions equations, and the fitness function value of the chromosome is the objective value of fuzzy chance constrained programming model. Chromosome coding, selection, crossover and mutation operations are also studied. The feasibility of the model and the effectiveness of the algorithm are illustrated by simulation numerical examples. Some results under different probability level are presented and discussed.

Key words: supply chain management, joint replenishment problem, fuzzy chance constrained programming, triangular fuzzy number, genetic algorithm