Applications of fuzzy multiple criteria decision making methods in civil engineering: a state-of-the-art survey

    Zhi Wen Affiliation
    ; Huchang Liao   Affiliation
    ; Edmundas Kazimieras Zavadskas Affiliation
    ; Jurgita Antuchevičienė Affiliation


A variety of fuzzy multiple criteria decision making (MCDM) models have been proposed to solve complicated decision-making problems. Many applications have been achieved, especially in the field of civil engineering. To analyze the developments about the fuzzy MCDM methods and their applications in civil engineering in recent years and further explore the future research directions, this study conducts a state of the art survey in which 52 journal papers focusing on the applications of fuzzy MCDM models in civil engineering from 2016 to 2020 are reviewed. We respectively classify these articles according to research problems and research methods. Through the literature review, we get findings in terms of the most concerned decision-making problem, the most widely-used evaluation criterion and the most popular fuzzy MCDM model. Furthermore, we present four aspects of research challenges and corresponding future research directions in the field of civil engineering, which may be helpful for researchers and practitioners to further investigate.

Keyword : civil engineering, multiple criteria decision making, fuzzy set, fuzzy multiple criteria decision making, literature review

How to Cite
Wen, Z., Liao, H., Zavadskas, E. K., & Antuchevičienė, J. (2021). Applications of fuzzy multiple criteria decision making methods in civil engineering: a state-of-the-art survey. Journal of Civil Engineering and Management, 27(6), 358-371.
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Jul 15, 2021
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Abdel-malak, F. F., Issa, U. H., Miky, Y. H., & Osman, E. A. (2017). Applying decision-making techniques to civil engineering projects. Beni-Suef University Journal of Basic and Applied Sciences, 6(4), 326–331.

Afshari, A. R. (2017). Methods for selection of construction project manager: Case study. Journal of Construction Engineering and Management, 143(12), 06017003.

Alireza, M., & Abimbola, W. (2019). Key uncertainty events impacting on the completion time of highway construction projects. Frontiers of Engineering Management, 6, 275–298.

Amini, M., Zhang, B., & Chang, S. (2018). Selecting building designs with consideration of sustainability and resiliency. Journal of Architectural Engineering, 24(1), 04018001.

Andrić, J. M., & Lu, D. G. (2016). Risk assessment of bridges under multiple hazards in operation period. Safety Science, 83, 80–92.

Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), 141–164.

Boostani, A., Jolai, F., & Bozorgi-Amiri, A. (2018). Optimal location selection of temporary accommodation sites in Iran via a hybrid fuzzy multiple-criteria decision making approach. Journal of Urban Planning and Development, 144(4), 04018039.

Bruno, G., Esposito, E., Genovese, A., & Simpson, M. (2016). Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment. Expert Systems with Applications, 43, 271–285.

Chatterjee, K., Zavadskas, E. K., Tamošaitienė, J., Adhikary, K., & Kar, S. (2018). A hybrid MCDM technique for risk management in construction projects. Symmetry, 10(2), 46.

Chen, L., & Pan, W. (2016). BIM-aided variable fuzzy multicriteria decision making of low-carbon building measures selection. Sustainable Cities and Society, 27, 222–232.

Dahooie, J. H., Zavadskas, E. K., Abolhasani, M., Vanaki, A., & Turskis, Z. (2018). A novel approach for evaluation of projects using an interval-valued fuzzy additive ratio assessment (ARAS) method: A case study of oil and gas well drilling projects. Symmetry, 10(2), 45.

Ding, S. B., Wang, X. L., & Wang, H. Y. (2016). Engine selection based on utility theory. Transactions of Nanjing University of Aeronautics & Astronautics, 33(6), 639–646.

Ebrahiminejad, M., Shakeri, E., Ardeshir, A., & Zarandi, M. (2018). An object-oriented model for construction method selection in buildings using fuzzy information. Energy and Buildings, 178, 228–241.

El Chanati, H., El-Abbasy, M. S., Mosleh, F., Senouci, A., Abouhamad, M., Gkountis, I., Zayed, T., & Al-Derham, H. (2016). Multi-criteria decision making models for water pipelines. Journal of Performance of Constructed Facilities, 30(4), 04015090.

Erdoğan, M., & Kaya, İ. (2016). A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey. Applied Soft Computing, 39, 84–93.

Fallahpour, A., Wong, K. Y., Rajoo, S., Olugu, E. U., Nilashi, M., & Turskis, Z. (2020). A fuzzy decision support system for sustainable construction project selection: an integrated FPP-FIS model. Journal of Civil Engineering and Management, 26(3), 247–258.

Galende-Hernández, M., Menéndez, M., Fuente, M. J., & SainzPalmero, G. I. (2018). Monitor-While-Drilling-based estimation of rock mass rating with computational intelligence: The case of tunnel excavation front. Automation in Construction, 93, 325–338.

Gou, L. F., & Zhong, Y. (2019). A new fault diagnosis method based on attributes weighted neutrosophic set. IEEE Access, 7, 117740–117748.

Hafezalkotob, A., Hafezalkotob, A., Liao, H. C., & Herrera, F. (2020). Interval MULTIMOORA method integrating interval Borda rule and interval best-worst-method-based weighting model: Case study on hybrid vehicle engine selection. IEEE Transactions on Cybernetics, 50(3), 1157–1169.

Hatefi, S. M., & Tamošaitienė, J. (2019). An integrated fuzzy DEMATEL-fuzzy ANP model for evaluating construction projects by considering interrelationships among risk factors. Journal of Civil Engineering and Management, 25(2), 114–131.

Hocine, A., Zhuang, Z. Y., Kouaissah, N., & Li, D. C. (2020). Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions. European Journal of Operational Research, 285(2), 642–654.

Hosseini, S. T., Lale Arefi, S., Bitarafan, M., Abazarlou, S., & Zavadskas, E. K. (2016). Evaluation types of exterior walls to reconstruct Iran earthquake areas (Ahar Heris Varzeqan) by using AHP and fuzzy methods. International Journal of Strategic Property Management, 20(3), 328–340.

Huang, M., Zhang, X. L., Ren, R. X., Liao, H. C., Zavadskas, E. K., & Antuchevičienė, J. (2020). Energy-saving building program evaluation with an integrated method under linguistic environment. Journal of Civil Engineering and Management, 26(5), 447–458.

Ilbahar, E., Karaşan, A., Cebi, S., & Kahraman, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety Science, 103, 124–136.

Inti, S., & Tandon, V. (2017). Application of fuzzy preference– analytic hierarchy process logic in evaluating sustainability of transportation infrastructure requiring multicriteria decision making. Journal of Infrastructure Systems, 23(4), 04017014.

Issa, U. H., Miky, Y. H., & Abdel-Malak, F. F. (2019). A decision support model for civil engineering projects based on multi-criteria and various data. Journal of Civil Engineering and Management, 25(2), 100–113.

Jang, W., Lee, S. K., & Han, S. H. (2018). Sustainable performance index for assessing the green technologies in urban infrastructure projects. Journal of Management in Engineering, 34(2), 04017056.

Jato-Espino, D., Indacoechea-Vega, I., Gáspár, L., & Castro-Fresno, D. (2018). Decision support model for the selection of asphalt wearing courses in highly trafficked roads. Soft Computing, 22(22), 7407–7421.

Javadi, M., Saeedi, G., & Shahriar, K. (2017). Developing a new probabilistic approach for risk analysis, application in underground coal mining. Journal of Failure Analysis and Prevention, 17(5), 989–1010.

Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2018). A dynamic fuzzy approach based on the EDAS Method for multi-criteria subcontractor evaluation. Information, 9(3), 68.

Leśniak, A., Kubek, D., Plebankiewicz, E., Zima, K., & Belniak, S. (2018). Fuzzy AHP application for supporting contractors’ bidding decision. Symmetry, 10(11), 642.

Liang, R., Dong, Z. J., Sheng, Z. H., Wang, X. Y., & Wu, C. Z. (2017). Case study of selecting decision-making schemes in large-scale infrastructure projects. Journal of Infrastructure Systems, 23(4), 06017001. IS.1943-555X.0000364

Liao, H. C., & Wu, X. L. (2020). DNMA: a double normalizationbased multiple aggregation method for multi-expert multicriteria decision making. Omega, 94, 102058.

Liao, H. C., Xu, Z. S., & Zeng, X. J. (2014). Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making. Information Sciences, 271, 125–142.

Liao, H. C., Wu, X. L., Liang, X. D., Yang, J. B., Xu, D. L., & Herrera, F. (2018). A continuous interval-valued linguistic ORESTE method for multi-criteria group decision making. Knowledge-Based Systems, 153, 65–77.

Maghsoodi, A. I., & Khalilzadeh, M. (2017). Identification and evaluation of construction projects’ critical success factors employing fuzzy-TOPSIS approach. KSCE Journal of Civil Engineering, 22(5), 1593–1605.

Mahamadu, A. M., Manu, P., Mahdjoubi, L., Booth, C., Aigbavboa, C., & Abanda, F. H. (2019). The importance of BIM capability assessment. Engineering, Construction and Architectural Management, 27(1), 24–48.

Martin, H., Lewis, T. M., Petersen, A., & Peters, E. (2017). Cloudy with a chance of fuzzy: building a multicriteria uncertainty model for construction project delivery selection. Journal of Computing in Civil Engineering, 31(1), 04016046.

Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126–4148.

Mazher, K. M., Chan, A. P. C., Zahoor, H., Khan, M. I., & Ameyaw, E. E. (2018). Fuzzy integral–based risk-assessment approach for public–private partnership infrastructure projects. Journal of Construction Engineering and Management, 144(12), 04018111.

Mi, X. M., Tang, M., Liao, H. C., Shen, W. J., & Lev, B. (2019). The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what’s next? Omega, 87, 205–225.

Mohandes, S. R., Sadeghi, H., Mahdiyar, A., Durdyev, S., Banaitis, A., Yahya, K., & Ismail, S. (2020). Assessing construction labours’ safety level: a fuzzy MCDM approach. Journal of Civil Engineering and Management, 26(2), 175–188.

Nyongesa, H. O., Musumba, G. W., & Chileshe, N. (2017). Partner selection and performance evaluation framework for a construction-related virtual enterprise: a multi-agent systems approach. Architectural Engineering and Design Management, 13(5), 344–364.

Omar, T., Nehdi, M. L., & Zayed, T. (2017). Performance of NDT techniques in appraising condition of reinforced concrete bridge decks. Journal of Performance of Constructed Facilities, 31(6), 04017104.

Osei-Kyei, R., & Chan, A. P. C. (2017). Developing a project success index for public–private partnership projects in developing countries. Journal of Infrastructure Systems, 23(4), 04017028.

Owusu, E. K., Chan, A. P. C., Hosseini, M. R., & Nikmehr, B. (2020). Assessing procurement irregularities in the supplychain of Chanaian construction projects: A soft-computing approach. Journal of Civil Engineering and Management, 26(1), 66–82.

Pang, Q., Wang, H., & Xu, Z. S. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Science, 369, 128–143.

Patel, D. A., & Jha, K. N. (2017). Developing a process to evaluate construction project safety hazard index using the possibility approach in India. Journal of Construction Engineering and Management, 143(1), 04016081.

Plebankiewicz, E., & Kubek, D. (2016). Multicriteria selection of the building material supplier using AHP and fuzzy AHP. Journal of Construction Engineering and Management, 142(1), 04015057.

Plebankiewicz, E., Meszek, W., Zima, K., & Wieczorek, D. (2020). Probabilistic and fuzzy approaches for estimating the life cycle costs of buildings under conditions of exposure to risk. Sustainability, 12(1), 226.

RazaviAlavi, S., & AbouRizk, S. (2017). Genetic algorithmsimulation framework for decision making in construction site layout planning. Journal of Construction Engineering and Management, 143(1), 04016084.

Rezakhani, P., & Maghiar, M. (2019). Fuzzy analytical solution for activity duration estimation under uncertainty. ASCEASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 5(4), 04019014.

Rodríguez, R. M., Martinez, L., & Herrera, F. (2012). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109–119.

Satapathy, S., Kumar, S., Garanayak, A., & Pani, A. (2018). An analysis of physical disorders of workers at construction site: a fuzzy-AHP ranking. International Journal of Business Excellence, 14(2), 212–239.

Smarandache, F. (2015). Symbolic neutrosophic theory.

Song, X. L., Zhong, L., Zhang, Z., Xu, J. P., Shen, C., & Peña-Mora, F. (2018). Multistakeholder conflict minimization-based layout planning of construction temporary facilities. Journal of Computing in Civil Engineering, 32(2), 04017080.

Taylan, O., Kabli, M. R., Porcel, C., & Herrera-Viedma, E. (2017). Contractor selection for construction projects using consensus tools and big data. International Journal of Fuzzy Systems, 20(4), 1267–1281.

Tomczak, M., & Rzepecki, L. (2017). Evaluation of supply chain management systems used in civil engineering. IOP Conference Series: Materials Science and Engineering, 245, 072005.

Utama, W. P., Chan, A. P. C., Zahoor, H., Gao, R., & Jumas, D. Y. (2019). Making decision toward overseas construction projects. Engineering, Construction and Architectural Management, 26(2), 285–302.

Vo, K. D., Nguyen, P. T., & Phan, P. T. (2018). Job performance factors of civil engineers in Vietnam. Journal of Mechanics of Continua and Mathematical Sciences, 14(5), 571–575.

Wallenius, J., Dyer, J. S., Fishburn, P. C., Steuer, R. E., Zionts, S., & Deb, K. (2008). Multiple criteria decision making, multiattribute utility theory: Recent accomplishments and what lies ahead. Management Science, 54(7), 1336–1349.

Wang, T. K., & Piao, Y. (2019). Development of BIM-AR-based facility risk assessment and maintenance system. Journal of Performance of Constructed Facilities, 33(6), 04019068.

Wieczorek, D., Plebankiewicz, E., & Zima, K. (2019). Model estimation of the whole life cost of a building with respect to risk factors. Technological and Economic Development of Economy, 25(1), 20–38.

Wu, X. L., & Liao, H. C. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272, 1017–1027.

Xiao, Y., & Zhang, C. H. (2016). A new method for financial decision making under intuitionistic linguistic environment. Economic Computation and Economic Cybernetics Studies and Research, 50(3), 303–318.

Yoon, J. H., & Cha, H. S. (2018). Optimal FM strategy for commercial office buildings using fuzzy synthetic evaluation. Journal of Performance of Constructed Facilities, 32(3), 04018025.

Yu, Y., Darko, A., Chan, A. P. C., Chen, C., & Bao, F. Y. (2018). Evaluation and ranking of risk factors in transnational public-private partnerships projects: Case study based on the intuitionistic fuzzy analytic hierarchy process. Journal of Infrastructure Systems, 24(4), 04018028.

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338– 353.

Zavadskas, E., Antucheviciene, J., Vilutiene, T., & Adeli, H. (2017). Sustainable decision-making in civil engineering, construction and building technology. Sustainability, 10(2), 14.

Zhang, L., Ding, L., Wu, X., & Skibniewski, M. J. (2017). An improved Dempster–Shafer approach to construction safety risk perception. Knowledge-Based Systems, 132, 30–46.

Zhao, X. J., Chen, L., Pan, W., & Lu, Q. C. (2017). AHP-ANP– fuzzy integral integrated network for evaluating performance of innovative business models for sustainable building. Journal of Construction Engineering and Management, 143(8), 04017054.

Zolfaghari, S., & Mousavi, S. M. (2018). Construction-project risk assessment by a new decision model based on De-Novo multi-approaches analysis and hesitant fuzzy sets under uncertainty. Journal of Intelligent & Fuzzy Systems, 35(1), 639–649.

Zyoud, S. H., Kaufmann, L. G., Shaheen, H., Samhan, S., & Fuchs-Hanusch, D. (2016). A framework for water loss management in developing countries under fuzzy environment: Integration of fuzzy AHP with fuzzy TOPSIS. Expert Systems with Applications, 61, 86–105.