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

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Abstract

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
URI:	http://umpir.ump.edu.my/id/eprint/6625
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