Abstract
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).