A hybrid fuzzy-optimization method for modeling construction emissions

Construction emissions have become a major concern that has risen extensively in the last few decades. This paper introduces a building information modeling (BIM)-based model to evaluate the environmental and economic consequences of different project alternatives. The model calculates direct, indir...

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Main Authors: Mohamed Marzouk, Eslam Mohammed Abdelakder
Format: Article
Language:English
Published: Growing Science 2020-01-01
Series:Decision Science Letters
Subjects:
Online Access:http://www.growingscience.com/dsl/Vol9/dsl_2019_24.pdf
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author Mohamed Marzouk
Eslam Mohammed Abdelakder
author_facet Mohamed Marzouk
Eslam Mohammed Abdelakder
author_sort Mohamed Marzouk
collection DOAJ
description Construction emissions have become a major concern that has risen extensively in the last few decades. This paper introduces a building information modeling (BIM)-based model to evaluate the environmental and economic consequences of different project alternatives. The model calculates direct, indirect emissions and primary energy for the overall project life cycle. A hybrid fuzzy multi-objective non-dominated sorting genetic algorithm II (NSGA-II) problem is designed to model the uncertainties associated with the quantification of the judging attributes, and consequently to find the most sustainable materials by minimizing the objective functions; project duration, project life cycle cost, project overall emissions and total project primary energy. Finally, TOPSIS is applied to select the most sustainable material for each construction component among the set of Pareto optimal solutions. A case study of an academic building in Saudi Arabia is presented in order to exemplify the practical features of the proposed model.
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spelling doaj.art-d3042647d2f8403995225ad4a2b013592022-12-22T01:44:37ZengGrowing ScienceDecision Science Letters1929-58041929-58122020-01-019112010.5267/j.dsl.2019.9.002A hybrid fuzzy-optimization method for modeling construction emissionsMohamed MarzoukEslam Mohammed AbdelakderConstruction emissions have become a major concern that has risen extensively in the last few decades. This paper introduces a building information modeling (BIM)-based model to evaluate the environmental and economic consequences of different project alternatives. The model calculates direct, indirect emissions and primary energy for the overall project life cycle. A hybrid fuzzy multi-objective non-dominated sorting genetic algorithm II (NSGA-II) problem is designed to model the uncertainties associated with the quantification of the judging attributes, and consequently to find the most sustainable materials by minimizing the objective functions; project duration, project life cycle cost, project overall emissions and total project primary energy. Finally, TOPSIS is applied to select the most sustainable material for each construction component among the set of Pareto optimal solutions. A case study of an academic building in Saudi Arabia is presented in order to exemplify the practical features of the proposed model.http://www.growingscience.com/dsl/Vol9/dsl_2019_24.pdfConstruction emissionsBuilding information modellingFuzzyNon-dominated sorting genetic algorithm IITOPSIS
spellingShingle Mohamed Marzouk
Eslam Mohammed Abdelakder
A hybrid fuzzy-optimization method for modeling construction emissions
Decision Science Letters
Construction emissions
Building information modelling
Fuzzy
Non-dominated sorting genetic algorithm II
TOPSIS
title A hybrid fuzzy-optimization method for modeling construction emissions
title_full A hybrid fuzzy-optimization method for modeling construction emissions
title_fullStr A hybrid fuzzy-optimization method for modeling construction emissions
title_full_unstemmed A hybrid fuzzy-optimization method for modeling construction emissions
title_short A hybrid fuzzy-optimization method for modeling construction emissions
title_sort hybrid fuzzy optimization method for modeling construction emissions
topic Construction emissions
Building information modelling
Fuzzy
Non-dominated sorting genetic algorithm II
TOPSIS
url http://www.growingscience.com/dsl/Vol9/dsl_2019_24.pdf
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