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    State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management

    Source: Journal of Water Resources Planning and Management:;2010:;Volume ( 136 ):;issue: 004
    Author:
    John Nicklow
    ,
    Patrick Reed
    ,
    Dragan Savic
    ,
    Tibebe Dessalegne
    ,
    Laura Harrell
    ,
    Amy Chan-Hilton
    ,
    Mohammad Karamouz
    ,
    Barbara Minsker
    ,
    Avi Ostfeld
    ,
    Abhishek Singh
    ,
    Emily Zechman
    DOI: 10.1061/(ASCE)WR.1943-5452.0000053
    Publisher: American Society of Civil Engineers
    Abstract: During the last two decades, the water resources planning and management profession has seen a dramatic increase in the development and application of various types of evolutionary algorithms (EAs). This observation is especially true for application of genetic algorithms, arguably the most popular of the several types of EAs. Generally speaking, EAs repeatedly prove to be flexible and powerful tools in solving an array of complex water resources problems. This paper provides a comprehensive review of state-of-the-art methods and their applications in the field of water resources planning and management. A primary goal in this ASCE Task Committee effort is to identify in an organized fashion some of the seminal contributions of EAs in the areas of water distribution systems, urban drainage and sewer systems, water supply and wastewater treatment, hydrologic and fluvial modeling, groundwater systems, and parameter identification. The paper also identifies major challenges and opportunities for the future, including a call to address larger-scale problems that are wrought with uncertainty and an expanded need for cross fertilization and collaboration among our field’s subdisciplines. Evolutionary computation will continue to evolve in the future as we encounter increased problem complexities and uncertainty and as the societal pressure for more innovative and efficient solutions rises.
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      State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management

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    contributor authorJohn Nicklow
    contributor authorPatrick Reed
    contributor authorDragan Savic
    contributor authorTibebe Dessalegne
    contributor authorLaura Harrell
    contributor authorAmy Chan-Hilton
    contributor authorMohammad Karamouz
    contributor authorBarbara Minsker
    contributor authorAvi Ostfeld
    contributor authorAbhishek Singh
    contributor authorEmily Zechman
    date accessioned2017-05-08T22:03:07Z
    date available2017-05-08T22:03:07Z
    date copyrightJuly 2010
    date issued2010
    identifier other%28asce%29wr%2E1943-5452%2E0000101.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/69907
    description abstractDuring the last two decades, the water resources planning and management profession has seen a dramatic increase in the development and application of various types of evolutionary algorithms (EAs). This observation is especially true for application of genetic algorithms, arguably the most popular of the several types of EAs. Generally speaking, EAs repeatedly prove to be flexible and powerful tools in solving an array of complex water resources problems. This paper provides a comprehensive review of state-of-the-art methods and their applications in the field of water resources planning and management. A primary goal in this ASCE Task Committee effort is to identify in an organized fashion some of the seminal contributions of EAs in the areas of water distribution systems, urban drainage and sewer systems, water supply and wastewater treatment, hydrologic and fluvial modeling, groundwater systems, and parameter identification. The paper also identifies major challenges and opportunities for the future, including a call to address larger-scale problems that are wrought with uncertainty and an expanded need for cross fertilization and collaboration among our field’s subdisciplines. Evolutionary computation will continue to evolve in the future as we encounter increased problem complexities and uncertainty and as the societal pressure for more innovative and efficient solutions rises.
    publisherAmerican Society of Civil Engineers
    titleState of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management
    typeJournal Paper
    journal volume136
    journal issue4
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0000053
    treeJournal of Water Resources Planning and Management:;2010:;Volume ( 136 ):;issue: 004
    contenttypeFulltext
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