A Comparison Of Genetic Algorithm With Simulated Annealing For Cell Formation Problem
key attributes of cellular manufacturing is the clustering of parts and machines into groups for maximizing machine utilization and minimizing operations performed outsides groups. In this research work manufacturing cell formation problem (CFP) is solved using two approaches i.e. Genetic Algorithm (GA) and Simulated Annealing (SA) with Grouping Efficacy (GE) as the fitness function. The performance of both approaches is measured through testing of 35 bench mark problems selected from literature. The comparative study shows that SA produced better results in 48.6% problems than GA. The computational time andstandard deviation of SA is lower than GA, further establishes the superiority of SA over GA for CFP solution.
KeyWords- Cellular Manufacturing, Genetic Algorithm, Simulated Annealing, Cell Formation Problem, Grouping Efficacy.