Performance evaluation of vector evaluated gravitational search algorithm
This paper presents a performance evaluation of a Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems. The VEGSA algorithm uses a number of populations of particles. In particular, a population of particles corresponds to one objective function to be min...
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Main Authors: | , , , , , , , , , |
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格式: | Article |
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ICIC Express Letters Office
2015
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在線閱讀: | http://eprints.utm.my/id/eprint/58791/ |
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總結: | This paper presents a performance evaluation of a Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems. The VEGSA algorithm 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. The results show that the VEGSA is outperformed by other multi-objective optimization algorithms and further enhancements are needed before it can be employed in any application. |
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