基于遗传粒子群混合算法的供应链调度优化  

Scheduling optimization in supply chain based on GA-PSO hybrid algorithm

作　　者：刘小华[1] 林杰[1] 

机构地区：[1]同济大学经济与管理学院,上海200092

出　　处：《控制与决策》2011年第4期501-506,共6页Control and Decision

基　　金：国家863计划项目(2007AA04Z151);国家自然科学基金重点项目(70531020);新世纪优秀人才支持计划项目(NCET-06-0377)

摘　　要：针对大规模定制模式下的供应链调度优化问题,首先将供应链调度优化问题进行数学规划建模,并通过一些定义将模型映射为有向图,以便于智能搜索算法的应用;然后,结合遗传算法全局搜索能力强与粒子群算法收敛速度快的特点,进行优势互补,构造了一种混合算法;最后,运用混合算法对供应链优化调度问题模型进行求解.通过与其他算法进行比较,所得结果表明混合算法有着更好的整体性能.For scheduling optimization problem in mass customization supply chain,a mathematical programming model is proposed,which is corresponded with a digraph via several definitions in order to use intelligent algorithm to solve it.A hybrid algorithm is proposed to optimize the objective function,which takes both advantages of genetic algorithm and particle swarm algorithm,so this hybrid algorithm integrated global searching ability with high convergence speed.Compared with the results of other algorithms,the simulation results show that the proposed algorithm is an efficient method for solving the scheduling optimization problem.

关 键 词：调度优化 混合算法 遗传算法 粒子群算法 

分 类 号：F273[经济管理—企业管理]