Performance evaluation of vector evaluated gravitational search algorithm

• Main Authors: Muhammad, B., Ibrahim, Z., Ghazali, K. H., Ghazali, M. R., Lim, K. S., Nawawi, S. W., Rahim, M. A. A., Aziz, N. A. A., Mubin, M., Mokhtar, N.
• Format: Article
• Published: ICIC Express Letters Office 2015
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/58791/

This paper presents a performance evaluation of a Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems. The VEGSA algorithm uses a number of populations of particles. In particular, a population of particles corresponds to one objective function to be minimized or maximized. Simultaneous minimization or maximization of every objective function is realized by exchanging a variable between populations. The results show that the VEGSA is outperformed by other multi-objective optimization algorithms and further enhancements are needed before it can be employed in any application.