MLGSA: Multi-Leader Gravitational Search Algorithm for Multi-Objective Optimization Problem

Authors

  • Mohd Riduwan Ghazali Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia
  • Khairul Hamimah Abas Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
  • Badaruddin Muhammad Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia
  • Nor Azlina Ab. Aziz Faculty of Engineering and Technology, Multimedia University, 75450 Melaka, Malaysia
  • Kian Sheng Lim Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia

Keywords:

—About Gravitational search algorithm, multiobjective optimization,

Abstract

Recently, we have introduced Multi-Leader Particle Swarm Optimization (MLPSO) algorithm for multiobjective optimization problem. Better convergence and diversity have been observed over the conventional MultiObjective Particle Swarm Optimization. In this paper, the same concept is extended to Gravitational Search Algorithm (GSA). The performance was investigated by solving a set of ZDT test problem. An analysis was also performed by varying the value of initial gravitational constant.

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Published

2017-03-15

How to Cite

Ghazali, M. R., Abas, K. H., Muhammad, B., Ab. Aziz, N. A., & Sheng Lim, K. (2017). MLGSA: Multi-Leader Gravitational Search Algorithm for Multi-Objective Optimization Problem. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(1-4), 119–123. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1792

Issue

Vol. 9 No. 1-4: Smart City Technology in Communication and Computer Engineering II

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

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