首页> 外文期刊>International Journal of Systems Science Operations & Logistics >An imperialist competitive algorithm in mixed-model assembly line sequencing problem to minimise unfinished works
【24h】

An imperialist competitive algorithm in mixed-model assembly line sequencing problem to minimise unfinished works

机译:混合模型装配线排序问题中的帝国主义竞争算法,可最大程度地减少未完成的工作

获取原文
获取原文并翻译 | 示例
       

摘要

Mixed-model assembly lines (MMALs) are a type of production lines where a variety of product models similar to product characteristics are assembled in a just-in-time production system. Usually, MMAL consists of a number of stations linked by a conveyor belt and each station has a work zone limited by upstream and downstream boundaries. To avoid improper interference between operators in the adjacent stations and excess of machine moving range, operators are forced to complete their operations within their predetermined work zone. There is a set of criteria on which to judge sequences of product models in terms of the effective utilisation of these lines. In this paper, the sequence of models for minimising the total unfinished work within their work zone is discussed. A novel imperialist competitive algorithm (ICA) is developed for solving this problem in small-, medium-and large-scale problems. The solutions obtained via ICA are compared against solutions obtained via B&B, a heuristic procedure, GRASP and BDP-2 in small problems, and also against a proposed genetic algorithm and a simulated annealing in small, medium and large problems. Experimental results show that this algorithm provides reasonably good solutions with low computational costs.
机译:混合模型装配线(MMAL)是一种生产线,其中在实时生产系统中装配了各种类似于产品特性的产品模型。通常,MMAL由通过传送带链接的多个工作站组成,每个工作站都有一个受上游和下游边界限制的工作区。为了避免相邻站点的操作员之间的不当干扰以及超出机器的移动范围,操作员被迫在其预定的工作区域内完成操作。有一组标准可以根据这些产品线的有效利用来判断产品模型的顺序。在本文中,讨论了在其工作区域内将未完成的总工作量最小化的模型序列。开发了一种新的帝国主义竞争算法(ICA)来解决小,中,大规模问题。将通过ICA获得的解决方案与通过B&B,启发式程序,GRASP和BDP-2获得的解决方案在小问题上进行比较,并且还与提出的遗传算法和在小,中,大问题上进行的模拟退火进行了比较。实验结果表明,该算法以较低的计算量提供了较好的解决方案。

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