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    Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization

    Source: Journal of Construction Engineering and Management:;2005:;Volume ( 131 ):;issue: 001
    Author:
    Daisy X. M. Zheng
    ,
    S. Thomas Ng
    ,
    Mohan M. Kumaraswamy
    DOI: 10.1061/(ASCE)0733-9364(2005)131:1(81)
    Publisher: American Society of Civil Engineers
    Abstract: Time–cost optimization (TCO) is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Although the TCO problem has been extensively examined, many research studies only focused on minimizing the total cost for an early completion. This does not necessarily convey any reward to the contractor. However, with the increasing popularity of alternative project delivery systems, clients and contractors are more concerned about the combined benefits and opportunities of early completion as well as cost savings. In this paper, a genetic algorithms
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      Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization

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    contributor authorDaisy X. M. Zheng
    contributor authorS. Thomas Ng
    contributor authorMohan M. Kumaraswamy
    date accessioned2017-05-08T20:40:13Z
    date available2017-05-08T20:40:13Z
    date copyrightJanuary 2005
    date issued2005
    identifier other%28asce%290733-9364%282005%29131%3A1%2881%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/22987
    description abstractTime–cost optimization (TCO) is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Although the TCO problem has been extensively examined, many research studies only focused on minimizing the total cost for an early completion. This does not necessarily convey any reward to the contractor. However, with the increasing popularity of alternative project delivery systems, clients and contractors are more concerned about the combined benefits and opportunities of early completion as well as cost savings. In this paper, a genetic algorithms
    publisherAmerican Society of Civil Engineers
    titleApplying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization
    typeJournal Paper
    journal volume131
    journal issue1
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/(ASCE)0733-9364(2005)131:1(81)
    treeJournal of Construction Engineering and Management:;2005:;Volume ( 131 ):;issue: 001
    contenttypeFulltext
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