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Real - valued constraint optimization with ICHEA

Sharma, Anuraganand and Sharma, Dharmendra P. (2012) Real - valued constraint optimization with ICHEA. In: Neural Information Processing. Lecture Notes in Computer Science, 7665 . Springer, Berlin Heidelberg, pp. 406-416. ISBN 978-3-642-34486-2

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    Abstract

    Intelligent constraint handling evolutionary algorithm (ICHEA) is a recently proposed variation of evolutionary algorithm (EA) that solves realvalued constraint satisfaction problems (CSPs) efficiently [20]. ICHEA has ability to extract and exploit information from constraints that guides its evolutionary search operators in contrast to traditional EAs that are ‘blind’ to constraints. Even its efficacy to solve CSPs it was not implemented to handle constraint optimization problems (COPs). This paper proposes an enhancement to ICHEA to solve real-valued COPs. The presented approach demonstrates very competitive results with other state-of-the-art approaches in terms of quality of solutions on well-known benchmark test problems.

    Item Type: Book Chapter
    Uncontrolled Keywords: embedded systems - high-performance network - multi-agent system - particle swarm optimization - statistical modeling
    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 13:20
    Last Modified: 05 Oct 2018 16:08
    URI: http://repository.usp.ac.fj/id/eprint/6849
    UNSPECIFIED

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