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改进交叉策略的GA在流水车间多目标调度中的应用 被引量：4

Application of GA with improved crossover operators in multi-objective flow shop scheduling
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摘要 根据流水车间的特点,建立了包含平均流通时间、生产周期、总的机器空闲时间、延误工件数量、总的延误时间和最大延误时间的多目标调度模型,并采用改进交叉策略的遗传算法进行仿真实验,实验结果表明模型是正确的,算法是有效的。 A multi-objective scheduling model is established inclusive of average circulation period,production period,total machine stand-by time,delayed volume of work,total delayed time,maximum delayed time based on the characteristics of flow shop.Also,an emulation experiment is carried out by means of genetic algorithm with improved crossover operators,the result of which proves that the model is correct and the algorithm is effective.
作者 秦艳
机构地区 沙洲职业工学院
出处 《现代制造工程》 CSCD 北大核心 2010年第12期29-32,共4页 Modern Manufacturing Engineering
关键词 流水车间 多目标优化 遗传算法 flow shop multi-objective optimization Genetic Algorithm（GA）
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献9

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二级参考文献8

  • 1王凌.车间调度及其遗传算法[M].北京:清华大学出版社,2002..
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共引文献47

同被引文献38

引证文献4

二级引证文献12

现代制造工程
2010年 第12期

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