Solution of discrete time-cost trade-off problem with adaptive search domain

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dc.authoridBirgonul, M. Talat/0000-0002-1638-2926
dc.contributor.authorBettemir, Onder Halis
dc.contributor.authorBirgonul, M. Talat
dc.date.accessioned2024-08-04T20:54:39Z
dc.date.available2024-08-04T20:54:39Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractPurposeExact solution of time-cost trade-off problem (TCTP) by the state-of-the-art meta-heuristic algorithms can be obtained for small- and medium-scale problems, while satisfactory results cannot be obtained for large construction projects. In this study, a hybrid heuristic meta-heuristic algorithm that adapts the search domain is developed to solve the large-scale discrete TCTP more efficiently.Design/methodology/approachMinimum cost slope-based heuristic network analysis algorithm (NAA), which eliminates the unfeasible search domain, is embedded into differential evolution meta-heuristic algorithm. Heuristic NAA narrows the search domain at the initial phase of the optimization. Moreover, activities with float durations higher than the predetermined threshold value are eliminated and then the meta-heuristic algorithm starts and searches the global optimum through the narrowed search space. However, narrowing the search space may increase the probability of obtaining a local optimum. Therefore, adaptive search domain approach is employed to make reintroduction of the eliminated activities to the design variable set possible, which reduces the possibility of converging into local minima.FindingsThe developed algorithm is compared with plain meta-heuristic algorithm with two separate analyses. In the first analysis, both algorithms have the same computational demand, and in the latter analysis, the meta-heuristic algorithm has fivefold computational demand. The tests on case study problems reveal that the developed algorithm presents lower total project costs according to the dependent t-test for paired samples with alpha = 0.0005.Research limitations/implicationsIn this study, TCTP is solved without considering quality or restrictions on the resources.Originality/valueThe proposed method enables to adapt the number of parameters, that is, the search domain and provides the opportunity of obtaining significant improvements on the meta-heuristic algorithms for other engineering optimization problems, which is the theoretical contribution of this study. The proposed approach reduces the total construction cost of the large-scale projects, which can be the practical benefit of this study.en_US
dc.identifier.doi10.1108/ECAM-06-2022-0601
dc.identifier.issn0969-9988
dc.identifier.issn1365-232X
dc.identifier.scopus2-s2.0-85169802522en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1108/ECAM-06-2022-0601
dc.identifier.urihttps://hdl.handle.net/11616/101557
dc.identifier.wosWOS:001133511400001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherEmerald Group Publishing Ltden_US
dc.relation.ispartofEngineering Construction and Architectural Managementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectProject schedulingen_US
dc.subjectDifferential evolutionen_US
dc.subjectMeta-heuristic algorithmen_US
dc.subjectTime-cost trade-off problemen_US
dc.subjectOptimizationen_US
dc.subjectUltraploidyen_US
dc.titleSolution of discrete time-cost trade-off problem with adaptive search domainen_US
dc.typeArticleen_US

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