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Monte Carlo-Enabled Dynamic Multiple-Criteria Decision Analysis for Selecting Sustainable Construction Methods: A Wind Farm Case Study
Evaluating the sustainability of various construction methods for one project during the bidding process can be extremely challenging. The challenge is caused by (1) the four overarching elements (i.e., criteria) within sustainability, namely environmental, economic, social, and technical aspects are conflicting, dynamic, and can change during the various construction phases; and (2) the general contractors are often required to make the most sustainable decision considering all four criteria with limited project information under a very tight timeline. The current practice relies on a simple multiple-criteria decision analysis (MCDA) to evaluate the conflicting criteria. Further, the literature review suggests no methods have been developed to evaluate the dynamic nature of the four criteria during different stages of the construction or to integrate multiple experts’ evaluations during the decision-making. To fill the gaps, this study developed a framework that will (1) enable dynamic evaluation of the four fundamental criteria of sustainability for different construction methods through a project’s entire construction duration and (2) integrate multiple experts’ inputs. Specifically, the proposed framework (1) extends the criteria value spaces by considering every criterion (and sub-criterion) as a time-dependent variable and (2) couples the MCDA with a Monte Carlo simulation to consider uncertainties while integrating various experts’ evaluations. The functionality and practicality of the proposed framework were demonstrated following an application to a wind farm project located in Northern Alberta. The results of the case study suggest the proposed Monte Carlo-enabled dynamic MCDA is capable of (1) evaluating the dynamic nature of each sustainability criterion for various construction methods throughout the construction duration; (2) considering uncertainties associated with each sustainability criterion and sub-criterion; (3) integrating various experts’ evaluations; and (4) providing a scientific decision-making approach for general contractors.
Monte Carlo-Enabled Dynamic Multiple-Criteria Decision Analysis for Selecting Sustainable Construction Methods: A Wind Farm Case Study
Evaluating the sustainability of various construction methods for one project during the bidding process can be extremely challenging. The challenge is caused by (1) the four overarching elements (i.e., criteria) within sustainability, namely environmental, economic, social, and technical aspects are conflicting, dynamic, and can change during the various construction phases; and (2) the general contractors are often required to make the most sustainable decision considering all four criteria with limited project information under a very tight timeline. The current practice relies on a simple multiple-criteria decision analysis (MCDA) to evaluate the conflicting criteria. Further, the literature review suggests no methods have been developed to evaluate the dynamic nature of the four criteria during different stages of the construction or to integrate multiple experts’ evaluations during the decision-making. To fill the gaps, this study developed a framework that will (1) enable dynamic evaluation of the four fundamental criteria of sustainability for different construction methods through a project’s entire construction duration and (2) integrate multiple experts’ inputs. Specifically, the proposed framework (1) extends the criteria value spaces by considering every criterion (and sub-criterion) as a time-dependent variable and (2) couples the MCDA with a Monte Carlo simulation to consider uncertainties while integrating various experts’ evaluations. The functionality and practicality of the proposed framework were demonstrated following an application to a wind farm project located in Northern Alberta. The results of the case study suggest the proposed Monte Carlo-enabled dynamic MCDA is capable of (1) evaluating the dynamic nature of each sustainability criterion for various construction methods throughout the construction duration; (2) considering uncertainties associated with each sustainability criterion and sub-criterion; (3) integrating various experts’ evaluations; and (4) providing a scientific decision-making approach for general contractors.
Monte Carlo-Enabled Dynamic Multiple-Criteria Decision Analysis for Selecting Sustainable Construction Methods: A Wind Farm Case Study
Lecture Notes in Civil Engineering
Desjardins, Serge (Herausgeber:in) / Poitras, Gérard J. (Herausgeber:in) / Nik-Bakht, Mazdak (Herausgeber:in) / Li, Kunkun (Autor:in) / Wu, Lingzi (Autor:in)
Canadian Society of Civil Engineering Annual Conference ; 2023 ; Moncton, NB, Canada
Proceedings of the Canadian Society for Civil Engineering Annual Conference 2023, Volume 3 ; Kapitel: 17 ; 233-246
16.10.2024
14 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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