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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 |
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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 |
Download Statistic: | View Download Statistics |
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