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基于遗传算法的柔性车间批量调度研究
引用本文:苑丽红,崔广才.基于遗传算法的柔性车间批量调度研究[J].长春理工大学学报,2005,28(3):11-13,3.
作者姓名:苑丽红  崔广才
作者单位:长春理工大学,计算机科学技术学院,长春,130022;长春理工大学,计算机科学技术学院,长春,130022
摘    要:针对一类柔性车间批量生产问题,提出了新的调度策略:区分工件的批量准备时间和加工时间;小批次调度策略.在此基础上,采用遗传算法作全局优化算法来实现最优调度,给出了批次调度策略下的遗传算法的编码、解码方案,以及一种特殊的交叉操作设计.仿真算例分析表明,一方面,所设计的遗传算法对解决柔性调度问题具有理想的效果,另一方面,在采用相同优化算法的前提下,分批次调度策略可以缩短工件的生产周期.

关 键 词:柔性制造系统  分批次调度  遗传算法
文章编号:1672-9870(2005)03-0011-03
收稿时间:2004-10-15
修稿时间:2004年10月15日

Study on Batch Splitting Scheduling of Flexible Workshop Based on Genetic Algorithm
YUAN Lihong,CUI Guangcai.Study on Batch Splitting Scheduling of Flexible Workshop Based on Genetic Algorithm[J].Journal of Changchun University of Science and Technology,2005,28(3):11-13,3.
Authors:YUAN Lihong  CUI Guangcai
Abstract:New strategy for the job-shop scheduling based on batch process of Flexible workshop is put forward.Firstly,the machine's setup time before a job arriving is separated from the job's producing time.Secondly,batch-splitting method is adopted.Then the genetic algorithm is introduced to optimize the whole scheduling and choose the best one.To explain this,this topic gives design of encoding,decoding and a special crossover operation for genetic algorithms based on batch process.From the given example we can draw a conclusion that genetic algorithm is very effective for solving job-shop scheduling,but even the same algorithm is used,batch splitting strategy can earn a less producing time.
Keywords:flexible manufacturing system  batch splitting scheduling  genetic algorithm
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