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Solving dynamic constraint optimization problems using ICHEA

Sharma, Anuraganand and Sharma, D.P. (2012) Solving dynamic constraint optimization problems using ICHEA. In: Neural Information Processing. Lecture Notes in Computer Science, 7665 . Springer International Publishing, Berlin, Heidelberg, pp. 434-444. ISBN 978-3-642-34486-2

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    Abstract

    Many real-world constrained problems have a set of predefined static constraints that can be solved by evolutionary algorithms (EAs) whereas some problems have dynamic constraints that may change over time or may be received by the problem solver at run time. Recently there has been some interest in academic research for solving continuous dynamic constraint optimization problems (DCOPs) where some new benchmark problems have been proposed. Intelligent constraint handling evolutionary algorithm (ICHEA) is demonstrated to be a versatile constraints guided EA for continuous constrained problems which efficiently solves constraint satisfaction problems (CSPs) in [22], constraint optimization problems (COPs) in [23] and dynamic constraint satisfaction problems (DCSPs) in [24]. We investigate efficiency of ICHEA in solving benchmark DCOPs and compare and contrast its performance with other well-known EAs.

    Item Type: Book Chapter
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Q Science > QA Mathematics > QA76 Computer software
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
    Depositing User: Anuraganand Sharma
    Date Deposited: 04 Oct 2013 13:37
    Last Modified: 18 Jan 2017 15:33
    URI: http://repository.usp.ac.fj/id/eprint/6853
    UNSPECIFIED

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