摘要
针对带分批约束的混合无等待流水加工环境中干扰事件的出现导致初始调度计划发生偏离的问题,研究如何运用干扰管理理论来应对工件变更扰动情况,建立了兼顾最小化工件完工时间加权和指标(初始调度目标)和最小化工件完工滞后时间加权和指标(偏离校正目标)的干扰管理调度模型,提出了双层微粒群优化策略与随机多邻域搜索机制相结合的混合求解算法。数值算例仿真实验结果表明,包含"插入-交换"大概率邻域搜索算子的混合微粒群优化算法求解本文所构建的干扰管理调度模型是有效的。
To solve the batch scheduling problem for a random or an anticipated job-change disruption in hybrid no-wait flow shop, a novel scheduling method based on disruption management is presented. The scheduling model is built considering both the target to minimize total weighted completion time （the original objective）and the target to minimize total weighted delay time （the disruption repairing objective）. By combining multi- objective approaching policy with the hi-level particle swarm optimization and stochastic probability multi-neigh- borhood search mechanism, a heuristic hybrid algorithm is proposed. The numerical experiments show that the hybrid PSO algorithm is effective to the disruption management-based scheduling model, including ＂ insert- change＂ great probability neighborhood search operator.
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2016年第3期246-254,共9页
Operations Research and Management Science
基金
国家自然科学基金重点项目(61533005)
国家科技支撑计划项目(2015BAF08B02)
教育部人文社会科学研究青年基金项目(11YJC630005)
中国博士后科学基金特别资助和面上项目(201104592
20100481222)
中央高校基本科研业务费资助(DUT14RW101)
关键词
运筹学
生产调度
干扰管理
微粒群优化算法
混合无等待流水线
operations research
production scheduling
disruption management
PSO algorithm
hybrid no-wait flow shop
