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机构地区:[1]广东工业大学广东省计算机集成制造系统重点实验室,广东广州510006
出 处:《计算机集成制造系统》2015年第4期1013-1022,共10页Computer Integrated Manufacturing Systems
基 金:国家自然科学基金资助项目(51205068;51175094;51375098);高等学校博士学科点专项科研基金资助项目(20124420120002);中国博士后科学基金资助项目(2012M520073;2013T60788);广东省自然科学基金资助项目(S2012040007784)~~
摘 要:为满足准时交货与节能生产的复合需求,构建了反映加权拖期、炉子装载水平和工件重量偏差程度的优化指标;建立了事件驱动调度机制,对机器完工和任务到达进行实时响应,并通过预测时间窗选取体现前摄性的调度任务集,同时采用"先分后合"的方式解耦工件族间的相互干扰;构造了启发式算法,在每个决策时刻进行滚动求解,基于任务到达时间组批,并用折衷规划计算各工件族的最佳批次,再综合评价确定全局最佳批次。仿真结果表明,与两类常用规则相比,所提方法具有明显的优越性。To satisfy the joint demand of punctual delivery and energy saving production, the optimization indexes re- flected the weighted tardiness, furnace loading rate and deviation degree of weights were proposed. An event-driven scheduling mechanism was developed to deal with the environment changes in real-time and to construct the schedu- ling jobs set by means of setting the look-ahead window proactively. Moreover, a "first separate after integrate" ap- proach was adopted to decouple the mutual interference between job families. A new heuristic algorithm was con- structed to solve the problem at each decision-making moment. Based on the arrival times of jobs for the batch for- mation, the best scenario for each job family was determined with compromising programming, and the global opti- mal scenario was determined by an evaluation function. The simulation experiments showed the superiority of pro- posed method by comparing with the benchmark control strategies. ,
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