A hybrid genetic algorithm for machine-part grouping

Authors:
Adnan Tariq;Iftikhar Hussain;Abdul Ghafoor
Affiliations:
Department of Mechanical Engineering, College of Electrical & Mechanical Engineering, National University of Science & Technology, Peshawar Road, Rawalpindi 4600, Pakistan;Department of Industrial Engineering, NWFP, University of Engineering and Technology, Peshawar, Pakistan;Department of Mechanical Engineering, College of Electrical & Mechanical Engineering, National University of Science & Technology, Peshawar Road, Rawalpindi 4600, Pakistan
Venue:
Computers and Industrial Engineering
Year:
2009

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Abstract

Cellular manufacturing (CM), which incorporates the flexibility of job shops and high production rate of flow lines, has been seen as a promising alternative for batch type production. Although CM provides great benefits, the design of CM is quite complex for real world problems. The main problem in the design of a CM is the formation of machine groups and corresponding part families. This paper aims at developing an approach that combines a local search heuristic (LSH) with genetic algorithm (GA). The approach has been tested on a number of problems from the literature. The results show that new approach not only converges to the best solution in the earlier generations but also produces solutions that are as accurate as any of the results reported, so far, in literature. Also, in certain cases the results produced by this technique are even better than the previously reported results.