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Developing a method to generate semi-distributed layouts by genetic algorithm

机译：开发一种通过遗传算法生成半分布式布局的方法

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摘要

Recent research in industries shows that existing layout configurations do not satisfy the needs of multiproduct enterprises in turbulent environments but within new layout strategies, distributed layouts have deserved more attention in most manufacturing environments and have a promising potential to cope with demand disturbances. This study is an attempt to design weighted distributed layouts via considering machine independent capabilities by a resource elements (REs) approach, which has caused generation of a new type of distributed layout named semi-distributed layout. REs are used to define processing requirements of parts and processing capabilities of machines. Another contribution of this paper is applying genetic algorithms (GAs) to distribute REs to find the optimal assignment of machines to available locations in such a way the travelled distances of parts are minimised and the accessibility of them to the required machines are maximised. The methodology of this paper is illustrated using a two-phase procedure. First, all machining facilities are divided into a set of REs based on their capabilities and second, the weighted connections among REs are considered to distribute them over the floor through implementing the developed GA. To evaluate the methodology, the proposed algorithm is tested with three illustrative examples obtained from the literature, in which two of them are comparable with outputs of simulated annealing (SA). The comparison between the outputs of the GA and the SA on the same cases presents that for large size problems, the GA significantly outperforms the SA.
机译：最近的行业研究表明，现有的布局配置不能在动荡的环境中满足多产品企业的需求，但是在新的布局策略中，分布式布局在大多数制造环境中都应引起更多关注，并且在应对需求扰动方面具有广阔的前景。这项研究是尝试通过考虑资源无关（RE）方法与机器无关的功能来设计加权分布式布局，这导致生成了一种新型的名为半分布式布局的分布式布局。 RE用于定义零件的加工要求和机器的加工能力。本文的另一项贡献是应用遗传算法（GA）分配RE，以将零件的行进距离最小化，并使零件对所需机器的可及性最大化，从而找到最佳的设备分配给可用位置。本文使用两个阶段的过程来说明方法。首先，将所有加工设施根据其功能划分为一组RE，其次，通过实施已开发的GA，可以考虑将RE之间的加权连接分布在整个地板上。为了评估该方法，使用从文献中获得的三个说明性示例对提出的算法进行了测试，其中两个示例与模拟退火（SA）的输出具有可比性。在相同情况下，GA和SA的输出之间的比较表明，对于大型问题，GA明显优于SA。

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  • 来源
    《International Journal of Production Research》 |2012年第4期|p.953-975|共23页
  • 作者

    Maryam Hamedi; Napsiah Bt. Ismail; Gholam Reza Esmaeilian; M.K.A. Ariffin;

  • 作者单位

    Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University Putra Malaysia 43400, Serdang, Selangor, Malaysia;

    Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University Putra Malaysia 43400, Serdang, Selangor, Malaysia;

    Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University Putra Malaysia 43400, Serdang, Selangor, Malaysia;

    Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University Putra Malaysia 43400, Serdang, Selangor, Malaysia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    semi-distributed layouts; resource element; genetic algorithm; optimisation;

    机译：半分布式布局;资源要素;遗传算法优化;

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