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改进遗传算法求解混合流水装配作业调度问题 被引量:4

Applying Improved Genetic Algorithm To Solve Hybrid Flow Shop Assembly Job Scheduling Problem
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摘要 研究了混合流水装配作业调度问题,并以液晶面板单元装配生产为例建立了数学模型,在充分考虑各约束条件的基础上,以最小化最大完工时间和及时交货为调度目标,提出一种使用精英保留策略的改进遗传算法对该问题进行求解,并给出了静态解码和贪婪解码两种解码算法。用不同的遗传策略和解码算法两两组合进行求解,并与其他方法进行比较,结果表明,采用精英保留和贪婪解码的遗传算法取得的值最优。 Thehybrid flow shop assembly job scheduling problemis resarched.As an example,the mathematical model of TFT Cell Assembly production scheduling problem is build.Based on the various constraint conditions and the target to minimize the maxi-mum completion timeand delivery in time,a improved genetic algorithm with elitist strategy is put forward. Static decode method and greedy decode method are proposed.Different evolution strategies and decode methods are combined with each other to solve the problem.The results of its comparsion with other methods show that the genetic algorithms with elitist strategy and greedy decode method performs the best.
作者 徐锋 步丰林
出处 《微型电脑应用》 2013年第9期58-61,共4页 Microcomputer Applications
关键词 装配作业调度 液晶面板 遗传算法 精英保留 Assembly Job Scheduling TFT Genetic Algorithm Elitist Strategy
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