Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/8778
Title: Controlling diversity of evolutionary algorithms
Authors: Nguyen, DHM
Wong, KP
Keywords: Adaptive control
Evolutionary computation
Issue Date: 2003
Publisher: IEEE
Source: 2003 International Conference on Machine Learning and Cybernetics, 2-5 November 2003, v. 2, p. 775-780 (CD-ROM) How to cite?
Abstract: This paper presents a control system based method for adapting the mutation step-size in order to control the diversity of the genome population. Population diversity is controlled so that it decreases exponentially with time in order to facilitate the linear order convergence that evolutionary algorithms are capable of. The paper restricts its attention to the application of unimodal search since linear order convergence of evolutionary algorithms has only been established analytically for unimodal and not for multimodal search. The case of multimodal search is left as an exercise in implementations of sub-population schemes. The paper also highlights the subtle but important difference between setting of EAs parameters and control of EAs performance.
URI: http://hdl.handle.net/10397/8778
ISBN: 0-7803-8131-9
DOI: 10.1109/ICMLC.2003.1259581
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