Abstract
To provide a fast robust optimizer for numerical solutions of inverse problems, a metaheuristic combining a clonal colony optimization methodology and a population based incremental learning method is proposed. In the proposed algorithm, a real-valued probability vector is introduced for the extension of each colony; a tournament-based mechanism is employed in a colony to destruct/discard plants to evolve the colony toward a promising space; and a new reallocation operator is designed. The numerical results on two case studies are reported to positively showcase the feasibilities and merits of the proposed metaheuristic.
Original language | English |
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Article number | 6749035 |
Journal | IEEE Transactions on Magnetics |
Volume | 50 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Feb 2014 |
Keywords
- Evolutionary computation
- inverse problem
- robustness
- uncertainty
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Electrical and Electronic Engineering