Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions

Badaruddin, Muhammad and Zuwairie, Ibrahim and Kamarul Hawari, Ghazali and Mohd Riduwan, Ghazali and Kian, Sheng Lim and Sophan Wahyudi, Nawawi and Nor Azlina, Ab. Aziz and Marizan, Mubin and Norrima, Mokhtar (2014) Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions. International Journal of Simulation: Systems, Science & Technology (IJSSST), 15 (1). pp. 1-6. ISSN 1473-8031 (print); 1473-804x (online). (Published)

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This paper presents a performance evaluation of Vector Evaluated Gravitational Search Algorithm (VEGSA), namely VEGSA-I and VEGSA-II algorithms, for multi-objective optimization problems. The VEGSA algorithms use 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. Performance evaluation is done based on ZDT test functions, which is a common benchmark problem for multiobjective optimization. The results shows that both VEGSA algorithms are outperformed by other multi-objective optimization algorithms and further enhancements are needed before it can be employed in any application.

Item Type: Article
Uncontrolled Keywords: Gravitational search algorithm; Multi-objective optimization problem
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 10 Sep 2014 03:08
Last Modified: 08 Feb 2018 03:45
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