| Autor: |
Ibrahim, Zuwairie, Muhammad, Badaruddin, Ghazali, Kamarul Hawari, Lim, Kian Sheng, Nawawi, Sophan Wahyudi, Yusof, Zulkifli Md. |
| Zdroj: |
2012 Fourth International Conference on Computational Intelligence, Modelling & Simulation; 1/ 1/2012, p13-17, 5p |
| Abstrakt: |
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. [ABSTRACT FROM PUBLISHER] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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