Development of SECA multi criteria decision making method to optimally select contractors for green construction projects (Case study for Iran)
This study aims to develop a multi-objective decision-making technique, called Simultaneous Evaluation of Criteria and Alternatives (SECA), to optimally rank green construction project contractors. The SECA approach is formulated as a multi-objective nonlinear programming problem comprising three ob...
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| Veröffentlicht in: | Results in control and optimization Jg. 21; S. 100617 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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01.12.2025
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| ISSN: | 2666-7207, 2666-7207 |
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| Abstract | This study aims to develop a multi-objective decision-making technique, called Simultaneous Evaluation of Criteria and Alternatives (SECA), to optimally rank green construction project contractors. The SECA approach is formulated as a multi-objective nonlinear programming problem comprising three objective functions: (1) maximizing the overall performance of alternatives, (2) minimizing the deviation of criteria weights from a reference point based on intra-criteria variation information, and (3) minimizing the deviation of criteria weights based on inter-criteria variation information, subject to two constraints on criteria weights. To implement the method, 16 key contractor prequalification criteria were first identified, followed by the selection of 10 qualified applicants. A decision matrix was constructed, and reference points were calculated. Variable weights for criteria and rankings of alternatives were obtained by coding the SECA method in Lingo software, considering different values of β. Determining the optimal β was a critical step, with values ranging from 0.1 to 7 evaluated. Results indicated that the maximum objective function value of 0.786 was achieved at β = 6, with the weight effect of the proposed price criterion being 0.0737. Contractor A3, with a score of 0.8887, was identified as the top-ranked contractor. Overall, the findings indicate that the SECA-based optimization method not only supports decision-makers in improving quality and reducing costs but also enhances transparency and trust in the selection process. By simultaneously evaluating criteria and alternatives and determining objective weights based on standard deviation and inter-criteria correlations, the method strengthens both transparency and reliability through reproducible and comparable analyses. |
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| AbstractList | This study aims to develop a multi-objective decision-making technique, called Simultaneous Evaluation of Criteria and Alternatives (SECA), to optimally rank green construction project contractors. The SECA approach is formulated as a multi-objective nonlinear programming problem comprising three objective functions: (1) maximizing the overall performance of alternatives, (2) minimizing the deviation of criteria weights from a reference point based on intra-criteria variation information, and (3) minimizing the deviation of criteria weights based on inter-criteria variation information, subject to two constraints on criteria weights. To implement the method, 16 key contractor prequalification criteria were first identified, followed by the selection of 10 qualified applicants. A decision matrix was constructed, and reference points were calculated. Variable weights for criteria and rankings of alternatives were obtained by coding the SECA method in Lingo software, considering different values of β. Determining the optimal β was a critical step, with values ranging from 0.1 to 7 evaluated. Results indicated that the maximum objective function value of 0.786 was achieved at β = 6, with the weight effect of the proposed price criterion being 0.0737. Contractor A3, with a score of 0.8887, was identified as the top-ranked contractor. Overall, the findings indicate that the SECA-based optimization method not only supports decision-makers in improving quality and reducing costs but also enhances transparency and trust in the selection process. By simultaneously evaluating criteria and alternatives and determining objective weights based on standard deviation and inter-criteria correlations, the method strengthens both transparency and reliability through reproducible and comparable analyses. |
| ArticleNumber | 100617 |
| Author | Ehsanifar, Mohammad Mirhosseini, S․Mohammad Moayeripour, S․Ali Zeighami, Ehsanollah |
| Author_xml | – sequence: 1 givenname: S․Ali surname: Moayeripour fullname: Moayeripour, S․Ali organization: Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran – sequence: 2 givenname: S․Mohammad surname: Mirhosseini fullname: Mirhosseini, S․Mohammad email: mo.mirhosseini@iau.ac.ir organization: Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran – sequence: 3 givenname: Mohammad surname: Ehsanifar fullname: Ehsanifar, Mohammad organization: Department of Industrial Engineering, Arak Branch, Islamic Azad University, Arak, Iran – sequence: 4 givenname: Ehsanollah surname: Zeighami fullname: Zeighami, Ehsanollah organization: Department of Civil Engineering, Arak Branch, Islamic Azad University, Arak, Iran |
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| Cites_doi | 10.1002/mma.7228 10.1061/(ASCE)0733-9364(2006)132:9(998) 10.1108/ECAM-10-2019-0543 10.3992/jgb.2.3.106 10.1108/MD-05-2017-0458 10.15388/Informatica.2018.167 10.3390/math10030523 10.1002/mma.7305 10.3390/su9101888 10.1080/15623599.2020.1868092 10.1080/014461900407356 10.1016/j.jclepro.2021.129041 10.1007/s13198-024-02249-3 10.1080/014461997373088 10.1061/JCEMD4.COENG-13305 10.1080/014461998371944 10.1016/j.autcon.2013.05.004 10.1139/L07-127 10.1007/s12205-022-1377-6 10.1080/13467581.2022.2087657 10.1007/s40815-017-0312-3 10.1016/j.ijproman.2012.05.004 10.1080/15623599.2019.1610545 10.3846/jcem.2010.05 10.1016/j.ijproman.2008.03.002 10.1109/EMR.2010.5497026 10.7763/LNSE.2014.V2.128 10.1080/10286608.2012.749871 10.1080/0144619042000202852 10.1016/j.proeng.2015.10.064 10.1016/j.chaos.2023.113834 10.1007/s40030-018-0271-1 10.3934/jimo.2024055 10.1016/j.jenvman.2006.12.025 10.1080/01446190902759009 10.1061/(ASCE)0733-9364(2004)130:3(385) 10.1007/s10479-024-05898-6 10.1061/(ASCE)CO.1943-7862.0000488 10.3390/buildings14061861 10.1108/ECAM-01-2016-0013 10.31181/oresta20303048k 10.1016/j.habitatint.2015.01.005 |
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| Keywords | Optimal contractor selection Multi-objective nonlinear programming Iran Simultaneous evaluation of criteria and alternatives (SECA) Overall performance optimization of options Green construction projects |
| Language | English |
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| SubjectTerms | Green construction projects Iran Multi-objective nonlinear programming Optimal contractor selection Overall performance optimization of options Simultaneous evaluation of criteria and alternatives (SECA) |
| Title | Development of SECA multi criteria decision making method to optimally select contractors for green construction projects (Case study for Iran) |
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