Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems

• Main Authors: Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof
• Format: Conference or Workshop Item
• Language: English
• Published: IEEE 2012
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/26988/1/Vector%20Evaluated%20Gravitational%20Search%20Algorithm%20%28VEGSA%29%20.pdf; http://umpir.ump.edu.my/id/eprint/26988/; https://doi.org/10.1109/CIMSim.2012.29

This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), 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. Two versions of VEGSA algorithm are presented in this study. Convex and non-convex test functions on biobjective optimization problems are used to evaluate the effectiveness of the proposed VEGSA.