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Title: A new implementation of population based incremental learning method for optimizations in electromagnetics
Authors: Yang, S
Ho, SL 
Ni, G
Machado, JM
Wong, KF
Keywords: Genetic algorithm (GA)
Global optimization
Inverse problem
Population based incremental learning (PBIL) method
Issue Date: Apr-2007
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on magnetics, Apr. 2007, v. 43, no. 4, p. 1601-1604 How to cite?
Journal: IEEE transactions on magnetics 
Abstract: To enhance the global search ability of population based incremental learning (PBIL) methods, it is proposed that multiple probability vectors are to be included on available PBIL algorithms. The strategy for updating those probability vectors and the negative learning and mutation operators are thus re-defined correspondingly. Moreover, to strike the best tradeoff between exploration and exploitation searches, an adaptive updating strategy for the learning rate is designed. Numerical examples are reported to demonstrate the pros and cons of the newly implemented algorithm.
ISSN: 0018-9464 (print)
1941-0069 (online)
DOI: 10.1109/TMAG.2006.892112
Rights: © 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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