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Multi - island competitive cooperative coevolution for real parameter global optimization

Bali , Kavitesh and Chandra, Rohitash (2015) Multi - island competitive cooperative coevolution for real parameter global optimization. In: Neural Information Processing. Lecture Notes in Computer Science, 9491 . Springer International Publishing, Istanbul, Turkey , pp. 127-136. ISBN 978-3-319-26554-4

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    Abstract

    Problem decomposition is an important attribute of cooperative coevolution that depends on the nature of the problems in terms of separability which is defined by the level of interaction amongst decision variables. Recent work in cooperative coevolution featured competition and collaboration of problem decomposition methods that was implemented as islands in a method known as competitive island cooperative coevolution (CICC). In this paper, a multi-island competitive cooperative coevolution algorithm (MICCC) is proposed in which several different problem decomposition strategies are given a chance to compete, collaborate and motivate other islands while converging to a common solution. The performance of MICCC is evaluated on eight different benchmark functions and are compared with CICC where only two islands were utilized. The results from the experimental analysis show that competition and collaboration of several different island can yield solutions with a quality better than the two-island competition algorithm (CICC) on most complex multi-modal problems.

    Item Type: Book Chapter
    Additional Information: Doi: 10.1007/978-3-319-26555-1_15
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
    Depositing User: Rohitash Chandra
    Date Deposited: 10 Mar 2016 16:20
    Last Modified: 06 Sep 2016 13:04
    URI: http://repository.usp.ac.fj/id/eprint/8428
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