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Article: Two-list genetic algorithm for optimizing work package schemes to minimize project costs

TitleTwo-list genetic algorithm for optimizing work package schemes to minimize project costs
Authors
KeywordsGenetic algorithm
Project planning
Stochastic task duration
Work breakdown structure
Work package scheme
Issue Date1-Sep-2024
PublisherElsevier
Citation
Automation in Construction, 2024, v. 165 How to Cite?
Abstract

Optimizing work package schemes is challenging under uncertain task duration. This paper develops a two-list genetic algorithm (TLGA) to optimize work package schemes with minimal project costs under deterministic and stochastic task durations. First, this paper defines the deterministic and stochastic work package scheme problem. Second, the TLGA, comprising a task and a work packaging list, is developed to generate the deterministic work package scheme and issue work package policies through stochastic distribution simulations. Moreover, a graphical user interface with TLGA is developed to enhance its practical application. Finally, experiments show that the TLGA can reduce the total cost by up to 19.57% in the deterministic problem, and the minimum gap between the TLGA and the state-of-the-art heuristics is only 3.91%. However, the TLGA can reduce the running time by about 66%. In the stochastic problem, this paper analyzes the impact of stochastic distributions on work package policies.


Persistent Identifierhttp://hdl.handle.net/10722/344573
ISSN
2023 Impact Factor: 9.6
2023 SCImago Journal Rankings: 2.626

 

DC FieldValueLanguage
dc.contributor.authorZhang, Yaning-
dc.contributor.authorLi, Xiao-
dc.contributor.authorTeng, Yue-
dc.contributor.authorBai, Sijun-
dc.contributor.authorChen, Zhi-
dc.date.accessioned2024-07-31T06:22:17Z-
dc.date.available2024-07-31T06:22:17Z-
dc.date.issued2024-09-01-
dc.identifier.citationAutomation in Construction, 2024, v. 165-
dc.identifier.issn0926-5805-
dc.identifier.urihttp://hdl.handle.net/10722/344573-
dc.description.abstract<p>Optimizing work package schemes is challenging under uncertain task duration. This paper develops a two-list genetic algorithm (TLGA) to optimize work package schemes with minimal project costs under deterministic and stochastic task durations. First, this paper defines the deterministic and stochastic work package scheme problem. Second, the TLGA, comprising a task and a work packaging list, is developed to generate the deterministic work package scheme and issue work package policies through stochastic distribution simulations. Moreover, a graphical user interface with TLGA is developed to enhance its practical application. Finally, experiments show that the TLGA can reduce the total cost by up to 19.57% in the deterministic problem, and the minimum gap between the TLGA and the state-of-the-art heuristics is only 3.91%. However, the TLGA can reduce the running time by about 66%. In the stochastic problem, this paper analyzes the impact of stochastic distributions on work package policies.<br></p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofAutomation in Construction-
dc.subjectGenetic algorithm-
dc.subjectProject planning-
dc.subjectStochastic task duration-
dc.subjectWork breakdown structure-
dc.subjectWork package scheme-
dc.titleTwo-list genetic algorithm for optimizing work package schemes to minimize project costs -
dc.typeArticle-
dc.identifier.doi10.1016/j.autcon.2024.105595-
dc.identifier.scopuseid_2-s2.0-85197079856-
dc.identifier.volume165-
dc.identifier.issnl0926-5805-

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