Multiple objective immune wolf colony algorithm for solving time-cost-quality trade-off problem

The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinea...

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Vydané v:	PloS one Ročník 18; číslo 2; s. e0278634
Hlavní autori:	Liu, Guanyi, Li, Xuemei, Alam, Khalid Mehmood
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Public Library of Science 09.02.2023 Public Library of Science (PLoS)
Predmet:	Algorithms Analysis Biology and Life Sciences Colonies Construction industry Cost benefit analysis Critical path Crystal structure Economic aspects Efficiency Engineering and Technology Evaluation Facility Design and Construction Genetic algorithms Integer programming Linear programming Mathematical optimization Medicine and Health Sciences Motivation Multiple objective analysis Nonlinear Dynamics Optimization Optimization algorithms Physical Sciences Planning Project engineering Project management Research and Analysis Methods Search process Social Sciences Tradeoffs Urbanization China
ISSN:	1932-6203, 1932-6203
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Abstract	The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinear relationship between quality and time, a nonlinear time-cost quality model is established. Meanwhile, in order to better solve the time-cost-quality trade-off problem, a multi-objective immune wolf colony optimization algorithm has been proposed. The hybrid method combines the fast convergence of the wolf colony algorithm and the excellent diversity of the immune algorithm to improve the accuracy of the wolf colony search process. Finally, a railway construction project is taken as an example to prove the effectiveness of the method.
AbstractList	The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinear relationship between quality and time, a nonlinear time-cost quality model is established. Meanwhile, in order to better solve the time-cost-quality trade-off problem, a multi-objective immune wolf colony optimization algorithm has been proposed. The hybrid method combines the fast convergence of the wolf colony algorithm and the excellent diversity of the immune algorithm to improve the accuracy of the wolf colony search process. Finally, a railway construction project is taken as an example to prove the effectiveness of the method. The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinear relationship between quality and time, a nonlinear time-cost quality model is established. Meanwhile, in order to better solve the time-cost-quality trade-off problem, a multi-objective immune wolf colony optimization algorithm has been proposed. The hybrid method combines the fast convergence of the wolf colony algorithm and the excellent diversity of the immune algorithm to improve the accuracy of the wolf colony search process. Finally, a railway construction project is taken as an example to prove the effectiveness of the method.The importance of the time-cost-quality trade-off problem in construction projects has been widely recognized. Its goal is to minimize time and cost and maximize quality. In this paper, the bonus-penalty mechanism is introduced to improve the traditional time-cost model, and considering the nonlinear relationship between quality and time, a nonlinear time-cost quality model is established. Meanwhile, in order to better solve the time-cost-quality trade-off problem, a multi-objective immune wolf colony optimization algorithm has been proposed. The hybrid method combines the fast convergence of the wolf colony algorithm and the excellent diversity of the immune algorithm to improve the accuracy of the wolf colony search process. Finally, a railway construction project is taken as an example to prove the effectiveness of the method.
Audience	Academic
Author	Alam, Khalid Mehmood Li, Xuemei Liu, Guanyi
AuthorAffiliation	1 Department of Economics and Management, Beijing Jiaotong University, Beijing, Beijing, China 2 China Study Centre, Karakoram International University, Gilgit -Baltistan, Pakistan Torrens University Australia, AUSTRALIA
AuthorAffiliation_xml	– name: Torrens University Australia, AUSTRALIA – name: 1 Department of Economics and Management, Beijing Jiaotong University, Beijing, Beijing, China – name: 2 China Study Centre, Karakoram International University, Gilgit -Baltistan, Pakistan
Author_xml	– sequence: 1 givenname: Guanyi orcidid: 0000-0003-1545-135X surname: Liu fullname: Liu, Guanyi – sequence: 2 givenname: Xuemei orcidid: 0000-0002-7787-1248 surname: Li fullname: Li, Xuemei – sequence: 3 givenname: Khalid Mehmood surname: Alam fullname: Alam, Khalid Mehmood
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/36757975$$D View this record in MEDLINE/PubMed
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CitedBy_id	crossref_primary_10_3390_su17051926 crossref_primary_10_1061_JCEMD4_COENG_14314 crossref_primary_10_1080_15623599_2024_2398267 crossref_primary_10_1080_01446193_2025_2502461
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SubjectTerms	Algorithms Analysis Biology and Life Sciences Colonies Construction industry Cost benefit analysis Critical path Crystal structure Economic aspects Efficiency Engineering and Technology Evaluation Facility Design and Construction Genetic algorithms Integer programming Linear programming Mathematical optimization Medicine and Health Sciences Motivation Multiple objective analysis Nonlinear Dynamics Optimization Optimization algorithms Physical Sciences Planning Project engineering Project management Research and Analysis Methods Search process Social Sciences Tradeoffs Urbanization
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Title	Multiple objective immune wolf colony algorithm for solving time-cost-quality trade-off problem
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