Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31441
Title: A robust metaheuristic combining clonal colony optimization and population-based incremental learning methods
Authors: Ho, SL 
Yang, S
Bai, Y
Huang, J
Keywords: Evolutionary computation
Inverse problem
Robustness
Uncertainty
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on magnetics, 2014, v. 50, no. 2, 6749035 How to cite?
Journal: IEEE transactions on magnetics 
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.
URI: http://hdl.handle.net/10397/31441
ISSN: 0018-9464
EISSN: 1941-0069
DOI: 10.1109/TMAG.2013.2283886
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