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

Zuwairie, Ibrahim and Badaruddin, Muhammad and Kamarul Hawari, Ghazali and Lim, Kian Sheng and Sophan Wahyudi, Nawawi and Zulkifli, Md. Yusof (2012) Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems. In: IEEE 4th International Conference on Computational Intelligence, Modelling and Simulation (CIMSim 2012), 25-27 September 2012 , Kuantan, Pahang Darul Makmur. pp. 13-17.. ISBN 978-1-4673-3113-5

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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.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: multi-objective optimization; VEGSA
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 22 Mar 2020 23:02
Last Modified: 22 Mar 2020 23:02
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