An integrated multi-objective optimization model for solving the construction time-cost trade-off problem

As construction projects become larger and more diversified, various factors such as time, cost, quality, environment, and safety that need to be considered make it very difficult to make the final decision. This study was conducted to develop an integrated Multi-Objective Optimization (iMOO) model...

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Main Authors: Choongwan Koo, Taehoon Hong, Sangbum Kim
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2015-02-01
Series:Journal of Civil Engineering and Management
Subjects:
Online Access:http://journals.vgtu.lt/index.php/JCEM/article/view/2971
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spelling doaj-e419155e7a2b412dad94769df27b3f052021-07-02T01:49:35ZengVilnius Gediminas Technical UniversityJournal of Civil Engineering and Management1392-37301822-36052015-02-0121310.3846/13923730.2013.802733An integrated multi-objective optimization model for solving the construction time-cost trade-off problemChoongwan Koo0Taehoon Hong1Sangbum Kim2Department of Architectural Engineering, Yonsei University, 120-749 Seoul, KoreaDepartment of Architectural Engineering, Yonsei University, 120-749 Seoul, KoreaDepartment of Civil and Environmental Engineering, Dongguk University, 100-715 Seoul, Korea As construction projects become larger and more diversified, various factors such as time, cost, quality, environment, and safety that need to be considered make it very difficult to make the final decision. This study was conducted to develop an integrated Multi-Objective Optimization (iMOO) model that provides the optimal solution set based on the concept of the Pareto front, through the following six steps: (1) problem statement; (2) definition of the optimization objectives; (3) establishment of the data structure; (4) standardization of the optimization objectives; (5) definition of the fitness function; and (6) introduction of the genetic algorithm. To evaluate the robustness and reliability of the proposed iMOO model, a case study on the construction time-cost trade-off problem was analyzed in terms of effectiveness and efficiency. The results of this study can be used: (1) to assess more than two optimization objectives, such as the initial investment cost, operation and maintenance cost, and CO2 emission trading cost; (2) to take advantage of the weights as the real meanings; (3) to evaluate the four types of fitness functions; and (4) to expand into other areas such as the indoor air quality, materials, and energy use. http://journals.vgtu.lt/index.php/JCEM/article/view/2971multi-objective optimizationpareto frontnon-dominated solutionfitness functionconstruction management
collection DOAJ
language English
format Article
sources DOAJ
author Choongwan Koo
Taehoon Hong
Sangbum Kim
spellingShingle Choongwan Koo
Taehoon Hong
Sangbum Kim
An integrated multi-objective optimization model for solving the construction time-cost trade-off problem
Journal of Civil Engineering and Management
multi-objective optimization
pareto front
non-dominated solution
fitness function
construction management
author_facet Choongwan Koo
Taehoon Hong
Sangbum Kim
author_sort Choongwan Koo
title An integrated multi-objective optimization model for solving the construction time-cost trade-off problem
title_short An integrated multi-objective optimization model for solving the construction time-cost trade-off problem
title_full An integrated multi-objective optimization model for solving the construction time-cost trade-off problem
title_fullStr An integrated multi-objective optimization model for solving the construction time-cost trade-off problem
title_full_unstemmed An integrated multi-objective optimization model for solving the construction time-cost trade-off problem
title_sort integrated multi-objective optimization model for solving the construction time-cost trade-off problem
publisher Vilnius Gediminas Technical University
series Journal of Civil Engineering and Management
issn 1392-3730
1822-3605
publishDate 2015-02-01
description As construction projects become larger and more diversified, various factors such as time, cost, quality, environment, and safety that need to be considered make it very difficult to make the final decision. This study was conducted to develop an integrated Multi-Objective Optimization (iMOO) model that provides the optimal solution set based on the concept of the Pareto front, through the following six steps: (1) problem statement; (2) definition of the optimization objectives; (3) establishment of the data structure; (4) standardization of the optimization objectives; (5) definition of the fitness function; and (6) introduction of the genetic algorithm. To evaluate the robustness and reliability of the proposed iMOO model, a case study on the construction time-cost trade-off problem was analyzed in terms of effectiveness and efficiency. The results of this study can be used: (1) to assess more than two optimization objectives, such as the initial investment cost, operation and maintenance cost, and CO2 emission trading cost; (2) to take advantage of the weights as the real meanings; (3) to evaluate the four types of fitness functions; and (4) to expand into other areas such as the indoor air quality, materials, and energy use.
topic multi-objective optimization
pareto front
non-dominated solution
fitness function
construction management
url http://journals.vgtu.lt/index.php/JCEM/article/view/2971
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