Threshold algorithm for the cell formation problem

T. R. Raguraman, R. Pandian, R. Kamalakannan
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引用次数: 1

Abstract

Advanced or smart manufacturing has recently been gaining increasing attention from the academia and industry in small and medium enterprises (SMEs). Smart manufacturing for Industry 4.0, which integrates resources, information, materials, and people to formulate a cyber physical system, has been the priority of many enterprises, especially those that are small and medium-sized. Threshold accepting algorithm is useful to resolve the cell formation problem which is based on the three perturbation techniques such as pair-wise exchange, insertion and random insertion perturbation schemes. This paper aims to maximise the grouping efficacy as it is one of the best performance measures for the cell formation problem. The performance evaluation of threshold accepting algorithm had actually been carried out after testing the benchmark problems of various literatures. This evaluation method proves that three perturbation schemes have the ability to sort out the cell formation problem. Among these three perturbation schemes, the random insertion perturbation scheme is providing better solutions than the others.
细胞形成问题的阈值算法
近年来,先进制造或智能制造越来越受到学术界和工业界对中小企业的关注。面向工业4.0的智能制造,将资源、信息、材料和人整合在一起,形成一个网络物理系统,已经成为许多企业,特别是中小型企业的优先事项。阈值接受算法用于解决基于三种摄动技术的细胞形成问题,即成对交换、插入和随机插入摄动方案。本文旨在最大限度地提高分组效率,因为它是对细胞形成问题的最佳性能措施之一。在测试了各种文献的基准问题后,实际对阈值接受算法进行了性能评价。该评价方法证明了三种摄动方案具有对细胞形成问题进行分选的能力。在这三种摄动方案中,随机插入摄动方案提供了较好的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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