基于仿真的多级供应链补货策略优化

深圳大学管理学院,广东深圳 518060

供应链管理; 第三方物流; 补货策略; 数量折扣; 仿真优化; 遗传算法

Simulation-based optimization of replenishment policy in multi-echelon supply chain
YANG Wen, PAN Yanchun, YIN Boteng, and LI Zhimin

College of Management, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China

supply chain management; third party logistics; replenishment policy; quantity discount pricing; simulation and optimization; genetic algorithm

DOI: 10.3724/SP.J.1249.2019.06689

备注

构造1个由多个供应商、1个配送中心、多个零售商和第三方物流公司组成的多级供应链,考虑顾客随机需求及第三方物流公司提供运输价格折扣情况下的补货策略问题.建立以供应链总成本最小为目标的数学规划模型,以及供应链仿真模型模拟供应链的运作过程,并将遗传算法与仿真模型结合.仿真结果表明,该仿真优化模型能够解决随机条件下复杂供应链的最优补货策略问题,为决策者提供借鉴.

By constructing a multi-echelon supply chain which is composed of multiple suppliers, a distribution center, and multiple retailers and a third-party logistics company, we consider the replenishment strategy problem under the condition that customers have random demand and the third-party logistics company provides transportation price discount for the transportation cost. We propose a mathematical programming model to minimize the total cost of the supply chain and develop a simulation model to simulate the operation of the supply chain system and combine genetic algorithm with the optimization algorithm. The simulated example shows that the proposed simulation-based optimization model can be used to solve the optimal replenishment problem in complex supply chain with uncertain demand, thus provides a basis of scientific decision for decision maker.

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