首页> 外文期刊>Journal of Intelligent Manufacturing >A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty
【24h】

A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty

机译:基于词典目标规划的不确定多目标车间遗传解决方案

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate the potential of the proposed multiobjective model and genetic algorithm.
机译:在这项工作中,我们考虑持续时间不确定且到期日明确的多目标作业车间问题。不良持续时间被建模为模糊数。我们采用模糊目标规划方法,以字典法最小化期望值为基础,提出了一个通用的多目标模型。为了解决由此产生的问题,我们提出了一种遗传算法,该算法在可能处于活动状态的时间表中进行搜索。提出了针对多个问题实例的实验结果,并由GA根据提出的模型解决了这些问题,并考虑了三个目标:延展时间,拖延和闲置。结果说明了所提出的多目标模型和遗传算法的潜力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号