Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach

Abstract Considering the construction industry holds ten percent on average in the gross national product over the world, the importance of efficient use of resources emerges. To alleviate the possibility of the risk factors and various uncertainties' negative impact on the project, the usage o...

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Autores principales:	Acar Yildirim,Hatice, Akcay,Cemil
Lenguaje:	English
Publicado:	Escuela de Construcción Civil, Pontificia Universidad Católica de Chile 2019
Materias:	Construction project time-cost optimization genetic algorithm fuzzy logic
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2019000300554
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spelling	oai:scielo:S0718-915X20190003005542020-02-04Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approachAcar Yildirim,HaticeAkcay,Cemil Construction project time-cost optimization genetic algorithm fuzzy logic Abstract Considering the construction industry holds ten percent on average in the gross national product over the world, the importance of efficient use of resources emerges. To alleviate the possibility of the risk factors and various uncertainties' negative impact on the project, the usage of the scheduling tools should be supported for planning as well as risk management. In today's construction perspective, the quality is not a primary objective; construction projects have to be completed within the cost and duration limits. During the construction progress, the inserting of extra activities affects to construction delays. Project success; from the planning stage to the completion of the building, it is possible to plan the resources, use them efficiently, and realize the determined time and cost objectives. In this study, a model is developed by using a fuzzy logic approach and genetic algorithm in order to provide time-cost optimization in construction projects under uncertainties. Firstly, fuzzy sets are used to take into account the effects of time and cost uncertainties on construction works. Fuzzy sets are used to model uncertainties, and the genetic algorithm is used to acquire minimum Project cost and duration. Thus, by establishing a fuzzy time-cost optimization model, optimum time-cost results are obtained according to different risk levels determined by the decision-makers. At the final stage, Pareto fronts from different risk levels that contain both minimum costs and durations are obtained and plotted.info:eu-repo/semantics/openAccessEscuela de Construcción Civil, Pontificia Universidad Católica de ChileRevista de la construcción v.18 n.3 20192019-12-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2019000300554en10.7764/rdlc.18.3.554
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Construction project time-cost optimization genetic algorithm fuzzy logic
spellingShingle	Construction project time-cost optimization genetic algorithm fuzzy logic Acar Yildirim,Hatice Akcay,Cemil Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
description	Abstract Considering the construction industry holds ten percent on average in the gross national product over the world, the importance of efficient use of resources emerges. To alleviate the possibility of the risk factors and various uncertainties' negative impact on the project, the usage of the scheduling tools should be supported for planning as well as risk management. In today's construction perspective, the quality is not a primary objective; construction projects have to be completed within the cost and duration limits. During the construction progress, the inserting of extra activities affects to construction delays. Project success; from the planning stage to the completion of the building, it is possible to plan the resources, use them efficiently, and realize the determined time and cost objectives. In this study, a model is developed by using a fuzzy logic approach and genetic algorithm in order to provide time-cost optimization in construction projects under uncertainties. Firstly, fuzzy sets are used to take into account the effects of time and cost uncertainties on construction works. Fuzzy sets are used to model uncertainties, and the genetic algorithm is used to acquire minimum Project cost and duration. Thus, by establishing a fuzzy time-cost optimization model, optimum time-cost results are obtained according to different risk levels determined by the decision-makers. At the final stage, Pareto fronts from different risk levels that contain both minimum costs and durations are obtained and plotted.
author	Acar Yildirim,Hatice Akcay,Cemil
author_facet	Acar Yildirim,Hatice Akcay,Cemil
author_sort	Acar Yildirim,Hatice
title	Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
title_short	Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
title_full	Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
title_fullStr	Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
title_full_unstemmed	Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
title_sort	time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach
publisher	Escuela de Construcción Civil, Pontificia Universidad Católica de Chile
publishDate	2019
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-915X2019000300554
work_keys_str_mv	AT acaryildirimhatice timecostoptimizationmodelproposalforconstructionprojectswithgeneticalgorithmandfuzzylogicapproach AT akcaycemil timecostoptimizationmodelproposalforconstructionprojectswithgeneticalgorithmandfuzzylogicapproach
_version_	1714206302888001536

Time-cost optimization model proposal for construction projects with genetic algorithm and fuzzy logic approach

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