Intelligent Systems in Optimizing Reservoir Operation Policy: A Review

Md Shabbir Hossain, A. El-shafie

    Research output: Contribution to journalArticle

    45 Citations (Scopus)

    Abstract

    The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.

    Original languageEnglish
    Pages (from-to)3387-3407
    Number of pages21
    JournalWater Resources Management
    Volume27
    Issue number9
    DOIs
    Publication statusPublished - Jul 2013

    Fingerprint

    Intelligent systems
    Evolutionary algorithms
    Dynamic programming
    Linear programming
    Artificial intelligence
    Genetic algorithms
    artificial intelligence
    linear programing
    genetic algorithm
    modeling
    policy
    Swarm intelligence

    Keywords

    • Evolutionary computations
    • Genetic algorithm
    • Reservoir operation
    • Swarm intelligence

    ASJC Scopus subject areas

    • Water Science and Technology
    • Civil and Structural Engineering

    Cite this

    Intelligent Systems in Optimizing Reservoir Operation Policy : A Review. / Hossain, Md Shabbir; El-shafie, A.

    In: Water Resources Management, Vol. 27, No. 9, 07.2013, p. 3387-3407.

    Research output: Contribution to journalArticle

    Hossain, Md Shabbir ; El-shafie, A. / Intelligent Systems in Optimizing Reservoir Operation Policy : A Review. In: Water Resources Management. 2013 ; Vol. 27, No. 9. pp. 3387-3407.
    @article{fb280f6e631a4421b5bddd1db194f880,
    title = "Intelligent Systems in Optimizing Reservoir Operation Policy: A Review",
    abstract = "The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.",
    keywords = "Evolutionary computations, Genetic algorithm, Reservoir operation, Swarm intelligence",
    author = "Hossain, {Md Shabbir} and A. El-shafie",
    year = "2013",
    month = "7",
    doi = "10.1007/s11269-013-0353-9",
    language = "English",
    volume = "27",
    pages = "3387--3407",
    journal = "Water Resources Management",
    issn = "0920-4741",
    publisher = "Springer Netherlands",
    number = "9",

    }

    TY - JOUR

    T1 - Intelligent Systems in Optimizing Reservoir Operation Policy

    T2 - A Review

    AU - Hossain, Md Shabbir

    AU - El-shafie, A.

    PY - 2013/7

    Y1 - 2013/7

    N2 - The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.

    AB - The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.

    KW - Evolutionary computations

    KW - Genetic algorithm

    KW - Reservoir operation

    KW - Swarm intelligence

    UR - http://www.scopus.com/inward/record.url?scp=84878764686&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84878764686&partnerID=8YFLogxK

    U2 - 10.1007/s11269-013-0353-9

    DO - 10.1007/s11269-013-0353-9

    M3 - Article

    AN - SCOPUS:84878764686

    VL - 27

    SP - 3387

    EP - 3407

    JO - Water Resources Management

    JF - Water Resources Management

    SN - 0920-4741

    IS - 9

    ER -