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    Weed Optimization Algorithm for Optimal Reservoir Operation

    Source: Journal of Irrigation and Drainage Engineering:;2016:;Volume ( 142 ):;issue: 002
    Author:
    Hamid-Reza Asgari
    ,
    Omid Bozorg Haddad
    ,
    Maryam Pazoki
    ,
    Hugo A. Loáiciga
    DOI: 10.1061/(ASCE)IR.1943-4774.0000963
    Publisher: American Society of Civil Engineers
    Abstract: This study introduces the weed optimization algorithm (WOA) to optimal reservoir operation. The WOA is a metaheuristic optimization method inspired by weeds’ life cycle. The effectiveness of the WOA is demonstrated with the optimization of mathematical functions and reservoir systems. The WOA is applied in continuous-time and discrete-time formulations of reservoir-operation optimization and its results are compared with global optimal solutions obtained with nonlinear programming (NLP), linear programming (LP), and the genetic algorithm (GA). The results show the WOA’s fast convergence to solutions that are very near the global optimal solutions of the reservoir optimization problems.
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      Weed Optimization Algorithm for Optimal Reservoir Operation

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    http://yetl.yabesh.ir/yetl1/handle/yetl/81506
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    contributor authorHamid-Reza Asgari
    contributor authorOmid Bozorg Haddad
    contributor authorMaryam Pazoki
    contributor authorHugo A. Loáiciga
    date accessioned2017-05-08T22:29:39Z
    date available2017-05-08T22:29:39Z
    date copyrightFebruary 2016
    date issued2016
    identifier other46757875.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/81506
    description abstractThis study introduces the weed optimization algorithm (WOA) to optimal reservoir operation. The WOA is a metaheuristic optimization method inspired by weeds’ life cycle. The effectiveness of the WOA is demonstrated with the optimization of mathematical functions and reservoir systems. The WOA is applied in continuous-time and discrete-time formulations of reservoir-operation optimization and its results are compared with global optimal solutions obtained with nonlinear programming (NLP), linear programming (LP), and the genetic algorithm (GA). The results show the WOA’s fast convergence to solutions that are very near the global optimal solutions of the reservoir optimization problems.
    publisherAmerican Society of Civil Engineers
    titleWeed Optimization Algorithm for Optimal Reservoir Operation
    typeJournal Paper
    journal volume142
    journal issue2
    journal titleJournal of Irrigation and Drainage Engineering
    identifier doi10.1061/(ASCE)IR.1943-4774.0000963
    treeJournal of Irrigation and Drainage Engineering:;2016:;Volume ( 142 ):;issue: 002
    contenttypeFulltext
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