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Multiobjective Symbiotic Search Algorithm Approaches for Electromagnetic Optimization.
- Source :
-
IEEE Transactions on Magnetics . Jun2017, Vol. 53 Issue 6, p1-4. 4p. - Publication Year :
- 2017
-
Abstract
- Optimization metaheuristics is a powerful way to deal with many electromagnetic optimization problems. Their main advantages are that they don’t require gradient computation, they are more likely to give a global optimum solution and have a higher degree of exploration and exploitation ability. Recently, the symbiotic organisms search (SOS) algorithm was proposed to solve single-objective optimization problems. SOS mimics the symbiotic relationship among the living beings. In order to extend the classical mono-objective SOS algorithm approach, this paper proposes a new multiobjective SOS (MOSOS) based on nondominance and crowding distance criterion. Furthermore, an improved MOSOS (IMOSOS) based on normal (Gaussian) probability distribution function also was proposed and evaluated. Results on a multiobjective constrained brushless direct current (dc) motor design show that the MOSOS and IMOSOS present promising performance. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189464
- Volume :
- 53
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Magnetics
- Publication Type :
- Academic Journal
- Accession number :
- 123392284
- Full Text :
- https://doi.org/10.1109/TMAG.2017.2665350