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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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