基于混合离散粒子群算法的非等同并行机分批调度研究  

Research on Batch Scheduling of Non-equivalent Parallel Machines Based on Hybrid Discrete Particle Swarm Optimization Algorithm

作　　者：徐兵[1] 潘沐 赵传宇 姜再龙 XU Bing;PAN Mu;ZHAO Chuanyu;JIANG Zailong(School of Mechanical and Electrical Engineering,Changchun University of Technology,Changchun 130012,China;Vitesco Automotive Changchun Co.,Ltd.,Changchun 130000,China)

机构地区：[1]长春工业大学机电工程学院,长春130012 [2]纬湃汽车电子(长春)有限公司,长春130000

出　　处：《机械工程师》2021年第12期8-10,14,共4页Mechanical Engineer

摘　　要：主要研究了n个可进行拆分的工件在m台非等同并行机上的加工调度问题,该问题主要包括3个方面:一是为每种工件进行合适的拆分计划;二是对拆分后的各子批统筹在各设备上的生产顺序;三是确定各设备的完工时间与所需生产成本。在生产过程中,不同的生产调度方案会导致总完工时间与生产成本的差异较大,因此从生产周期最短与调整成本最低出发构建多目标数学模型,采用混合离散粒子群算法进行算例分析与对比验证,求解出排产方案,结果表明该算法具有较好搜索能力与稳定性。This paper studies the processing scheduling problem of m non-identical parallel machines for n workpieces that can be split.The problem mainly includes three aspects.One is to make a suitable split plan for each kind of workpiece.The second is to coordinate the production sequence of each sub-batch after splitting on each equipment.The third is to determine the completion time and production cost of each equipment.In the production process,different production scheduling schemes will result in a large difference between the total completion time and the production cost.Therefore,starting from the shortest production cycle and the lowest adjustment cost,a multi-objective mathematical model is constructed,and the hybrid discrete particle swarm optimization algorithm is used for example analysis and comparison verification,and the production scheduling plan is solved.The results show that the algorithm has good search ability and stability.

关 键 词：混合离散粒子群算法 可拆分 并行机 多目标 

分 类 号：F406.2[经济管理—产业经济]