Solving Dynamic Constraint Optimization Problems Using ICHEA

Anurag Sharma, Dharmendra Sharma

    Research output: A Conference proceeding or a Chapter in BookConference contribution

    3 Citations (Scopus)

    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.
    Original languageEnglish
    Title of host publicationInternational Conference on Neural Information Processing (ICONIP 2012)
    Subtitle of host publicationLecture Notes in Computer Science
    EditorsTingwen Huang, Zhigang Zeng, Chuandong Li, C.S. Leung
    Place of PublicationBerlin
    PublisherSpringer
    Pages434-444
    Number of pages11
    Volume7665
    ISBN (Print)9783642344862
    DOIs
    Publication statusPublished - 2012
    Event19th International Conference on Neural Information Processing 2012 - Doha, Doha, Qatar
    Duration: 12 Nov 201215 Nov 2012

    Conference

    Conference19th International Conference on Neural Information Processing 2012
    CountryQatar
    CityDoha
    Period12/11/1215/11/12

    Fingerprint

    Evolutionary algorithms
    Constraint satisfaction problems

    Cite this

    Sharma, A., & Sharma, D. (2012). Solving Dynamic Constraint Optimization Problems Using ICHEA. In T. Huang, Z. Zeng, C. Li, & C. S. Leung (Eds.), International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science (Vol. 7665, pp. 434-444). Berlin: Springer. https://doi.org/10.1007/978-3-642-34487-9_53
    Sharma, Anurag ; Sharma, Dharmendra. / Solving Dynamic Constraint Optimization Problems Using ICHEA. International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. editor / Tingwen Huang ; Zhigang Zeng ; Chuandong Li ; C.S. Leung. Vol. 7665 Berlin : Springer, 2012. pp. 434-444
    @inproceedings{ff960419083b40428f3f533e073878b0,
    title = "Solving Dynamic Constraint Optimization Problems Using ICHEA",
    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.",
    keywords = "Dynamic constraint optimization problem, Intelligent constraint handling evolutionary algorithm, Evolutionary algorithms, dynamic constraint satisfaction problems",
    author = "Anurag Sharma and Dharmendra Sharma",
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    Sharma, A & Sharma, D 2012, Solving Dynamic Constraint Optimization Problems Using ICHEA. in T Huang, Z Zeng, C Li & CS Leung (eds), International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. vol. 7665, Springer, Berlin, pp. 434-444, 19th International Conference on Neural Information Processing 2012, Doha, Qatar, 12/11/12. https://doi.org/10.1007/978-3-642-34487-9_53

    Solving Dynamic Constraint Optimization Problems Using ICHEA. / Sharma, Anurag; Sharma, Dharmendra.

    International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. ed. / Tingwen Huang; Zhigang Zeng; Chuandong Li; C.S. Leung. Vol. 7665 Berlin : Springer, 2012. p. 434-444.

    Research output: A Conference proceeding or a Chapter in BookConference contribution

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    AU - Sharma, Anurag

    AU - Sharma, Dharmendra

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    AB - 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.

    KW - Dynamic constraint optimization problem

    KW - Intelligent constraint handling evolutionary algorithm

    KW - Evolutionary algorithms

    KW - dynamic constraint satisfaction problems

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    BT - International Conference on Neural Information Processing (ICONIP 2012)

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    Sharma A, Sharma D. Solving Dynamic Constraint Optimization Problems Using ICHEA. In Huang T, Zeng Z, Li C, Leung CS, editors, International Conference on Neural Information Processing (ICONIP 2012): Lecture Notes in Computer Science. Vol. 7665. Berlin: Springer. 2012. p. 434-444 https://doi.org/10.1007/978-3-642-34487-9_53