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 Waqas Javaid1*, Adnan Tariq1, Iftikhar Hussain2, Sahar Noor2

1* Department of Mechanical Engineering, Wah Engineering College, University of Wah, Quaid Avenue, Wah Cant,
Punjab 47040, Pakistan
2 Department of Industrial Engineering, University of Engineering & Technology, Peshawar, Pakistan 


Cellular Manufacturing Systems (CMS) have been widely considered as the most efficient manufacturing systems
in the case of medium variety and medium volume of production. The main advantage of CMS lies in the effective
grouping of parts into families and machines in to corresponding groups as it results in minimizing the number of
intercellular moves. Over the years, a number of efficient approaches have been developed by researchers to handle
the Cell Formation Problem (CFP). Among these, a large number of approaches consist of Artificial Intelligence
(AI) based techniques. The main advantage of such approaches is their ability to handle the CFP effectively both in
terms of accuracy and computational effort. Following the same trend an evolutionary algorithm has been developed
during this research by combining Standard Genetic Algorithm with a very effective Local Search Heuristic (LSH).
The results show that it is efficient both in terms accuracy and speed of convergence (CPU time). 


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Journal of Engineering and Applied Sciences


Vol. 39, Iss. 1, pp. 01-126


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