In this study three different methodologies are developed, (i) a similarity coefficient based approach is adopted to obtain the initial machine part grouping solution. Thereafter a state-of-the-art part clustering algorithm is proposed to improve the solution quality. (ii) A dissimilarity coefficient based approach is adopted to obtain the initial machine part grouping solution. Thereafter a novel approach based on a population based heuristic technique is proposed to improve the solution quality. (iii) A similarity coefficient based technique is exploited to form machine cells and part families. Thereafter a Simulated Annealing (SA) based metaheuristic algorithm is utilized to enhance the quality of the solutions obtained.

�ber die Autorin bzw. den Autor:

Tamal Ghosh is a PhD Research Scholar in the Department of Production Engineering, Jadavpur University, India. He has also obtained his Master of Technology (M.Tech) in Industrial Engineering from West Bengal University of Technology and Bachelor of Technology (B.Tech) in Computer Engineering from National Institute of Technology Calicut India.

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