Generalized Utilization-Based Similarity Coefficient for Machine-Part Grouping Problem in Cellular Manufacturing

IF 0.9 Q4 ENGINEERING, INDUSTRIAL
Tamal Ghosh
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引用次数: 1

Abstract

This article intends to justify the gap in the research of similarity coefficient driven approach- es and cell formation problems (CFP) based on ratio data in cellular manufacturing systems (CMS). The actual implication of ratio data was vaguely addressed in past literature, which has been corrected recently. This research considered that newly projected CFP based on ration data. This study further revealed the lack of interest of researchers in investigation for an appropriate and improved similarity coefficient primarily for CFP based on ratio data. For that matter a novel similarity coefficient named as Generalized Utilization-based Simi- larity Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter a two-stage cell formation technique is adopted. First, the proposed GUSC based method is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is proposed to obtain effective part families. This proposed approach is successfully verified on the test problems and compared with algorithms based on another similarity coefficient and a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.
基于广义利用的元胞制造机件分组问题相似系数
本文旨在弥补在元胞制造系统(CMS)中基于比率数据的相似系数驱动方法- es和细胞形成问题(CFP)研究中的空白。在过去的文献中,比率数据的实际含义是模糊的,最近得到了纠正。本研究考虑了基于定量数据的新预测CFP。本研究进一步揭示了研究人员对主要基于比率数据的CFP的适当和改进的相似系数缺乏兴趣。为此,提出了一种新的相似系数——基于广义利用的相似系数(GUSC),它能科学地处理比率数据。然后采用两阶段细胞形成技术。首先,采用基于GUSC的方法获得有效的机器单元。其次,提出了一种新的零件分配启发式算法来获取有效零件族。该方法成功地在测试问题上进行了验证,并与基于另一个相似系数和最近的元启发式算法的算法进行了比较。结果表明,本文提出的方法可获得66.67%的改进解。
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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来源期刊
CiteScore
2.80
自引率
21.40%
发文量
0
期刊介绍: Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.
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