基于改进粒子群算法的体育用品企业内部供应链优化

摘要

In this paper, in view of the multi-dimensionality and non-linearity of the internal supply chain of the sports utility enterprise and orienting toward maximizing customer satisfaction and enterprise interest, we built a multi-objective optimization model from an economic perspective which used order fulfillment rate as an index to measuring customer satisfaction. Then we used an improved particle swarm optimization process to solve the model and thus accurately and speedily locate the optimal decision. At the end, in connection with an empirical case, we had a simulation study which showed that the improved particle swarming optimization process could not only find the optimal solution quickly and balance the relations between local optimization and global optimization, but also it could optimize all indexes involved and achieve the goal of cost reduction.%针对体育用品企业内部供应链的多维、非线性问题,以客户满意度和企业利润最大化为导向,从经济学的角度构建了一个多目标优化模型,此模型把订单满足率作为衡量客户满意度的指标.模型定义为一个生产部门、多个配送中心、多个门店.在优化模型求解过程中,利用一种改进粒子群优化算法,从而快速准确的找到优化决策结果.最后通过具体算例进行仿真测试,结果表明改进粒子群优化算法不仅能够快速的找到最优解,平衡局部最优与全局最优关系,同时能够获得各项指标结果,达到降低成本的目的.