Measuring the performance of FCM versus PSO for fuzzy clustering problems

• Published in: International journal of industrial engineering computations Vol. 4; no. 3; pp. 387 - 392
• Main Authors: Jafari, Hamid Reza, Soltani, Amir Reza, Soltani, Mohammad Reza
• Format: Journal Article
• Language: English
• Published: Growing Science 01.07.2013
• Subjects: FCM; Fuzzy clustering; PSO; Xie-Beni
• ISSN: 1923-2926; 1923-2934
• DOI: 10.5267/j.ijiec.2013.03.005

Clustering cellular manufacturing plays an important role in many industrial engineering problems. This paper investigates the performance of two methods of heuristic and metaheuristics fuzzy clustering. The proposed method investigates heuristic well-known FCM and particle swarm optimization (PSO) on some well-known benchmarks. We use two criteria of J(P) as well as Xie-Beni to compare the results. Three parameters of PSO method is tuned using design of experiment and then the results of PSO are compared versus FCM method in terms of two mentioned criteria. The proposed models are run for each instance 10 different times and, using ANOVA test, the means of two methods are compared. While the results of ANOVA do not indicate any meaningful difference between PSO and FCM in terms of J(P), we have found some meaningful differences between PSO and FCM in terms of Xie-Beni criterion. In other words, PSO performs better than FCM in terms of Xie-Beni.