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

Mohd Riduwan, Ghazali and Khairul Hamimah, Abas and Badaruddin, Muhammad and Nor Azlina, Ab. Aziz and Kian, Sheng Lim (2017) MLGSA: Multi-­Leader Gravitational Search Algorithm for Multi­Objective Optimization Problem. In: International Conference on Information in Business and Technology Management (I2BM 2016) , 26-28 January 2016 , Melaka, Malaysia. pp. 1-6.. ISSN 1343-4500 (print); 1344-8994 (online)

Preview	PDF Multi-Leader Gravitational Search Algorithm For Multi-Objective Optimization Problem.pdf Download (39kB) | Preview
	PDF Multi-Leader Gravitational Search Algorithm For Multi-Objective Optimization Problem.pdf Restricted to Repository staff only Download (612kB) | Request a copy

Abstract

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

Item Type:	Conference or Workshop Item (Lecture)
Uncontrolled Keywords:	Gravitational search algorithm; multi-objective optimization
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Faculty of Electrical & Electronic Engineering
Depositing User:	Mrs. Neng Sury Sulaiman
Date Deposited:	18 Mar 2016 03:44
Last Modified:	15 Oct 2018 07:24
URI:	http://umpir.ump.edu.my/id/eprint/12015
Download Statistic:	View Download Statistics

Actions (login required)

View Item