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Genetic rule based techniques in cellular manufacturing (1992-2010): a systematic survey

T Ghosh, P Dan, S Sengupta, M Chattopadhyay

Abstract


Genetic algorithm is believed to be the most robust unbiased stochastic search algorithm for sampling a large solution space. Considering the steady convergence framework of genetic algorithm, it is intensely recognized in group technology applications in cellular manufacturing, and subsequently employed in part family construction, machine cluster formation and manufacturing cell designing since preceding two decades. This study demonstrates a substantial description of various genetic algorithm based techniques and its usage in manufacturing cell design problem and categorically emphasizes on the significance of the prompt propagation of genetic algorithm in cellular manufacturing and its empirical modifications in genetic operations which are evolving as an indispensable segment of managerial decision making. The sustained growth of genetic algorithm and its intricate practices such as managing multi-objective problems and forming hybrid procedures are the focus areas of this article. The major verdict of this research work is to identify the trend of genetic algorithm in cellular manufacturing system, which was started with very basic simple genetic algorithm in 1990 and gradually evolved with complex hybrid techniques in recent time.

Keywords: Cellular manufacturing, group technology, genetic algorithm, survey, review



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