Evaluation of infrastructure projects by a decision model based on RPR, MABAC, and WASPAS methods with interval-valued intuitionistic fuzzy sets
Abstract
Infrastructure projects (IPs) face numerous challenges to reach the predefined aims over their life-cycle. There are many difficulties in projects because of the variety of elements in project’s tendency and the dependency of the project on mainly national factors. Due to these difficulties and their practices, the projects meet with uncertainty. In this paper, an interval-valued intuitionistic fuzzy set (IVIFS) is used at identifying ambiguity in IPs. Also, a new multi-criteria decision-making (MCDM) model is presented to evaluate and select the suitable alternative in IPs. Hence, a new IVIF-relative preference alternative-multi-attributive border approximation area comparison (IVIF-RPR-MABAC), and IVIF-weighted aggregated sum product assessment (IVIF-WASPAS) are proposed in order to obtain the weights of decision makers (DMs) and criteria, and a new IVIF-RPR-MABAC method is proposed to rank the alternatives. In this paper, a combination of the three mentioned approaches creates proposed new hybrid model to evaluate the main factors and the projects. Furthermore, a real case study is applied from the literature to validate the efficiency and performance of the proposed model. Afterward, a comparative analysis is presented to validate the proposed approach by comparing the hybrid proposed model with two IVIF-TOPSIS and IVIF-extended-VIKOR methods. The final results confirm the efficiency of the proposed model in ranking the main alternatives of an MCDM problem. Moreover, the sensitivity analysis is reported to determine the affection of parameters on the final weighting and ranking outcomes.
Keyword : infrastructure projects, multi-criteria decision-making (MCDM), interval-valued intuitionistic fuzzy sets (IVIFSs), relative preference alternative (RPR) method, multi-attributive border approximation area comparison (MABAC) method, weighted aggregated sum product assessment (WASPAS) method
How to Cite
Salimian, S., Mousavi, S. M., & Antuchevičienė, J. (2022). Evaluation of infrastructure projects by a decision model based on RPR, MABAC, and WASPAS methods with interval-valued intuitionistic fuzzy sets. International Journal of Strategic Property Management, 26(2), 106-118. https://doi.org/10.3846/ijspm.2022.16476
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Keshavarz Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Esmaeili, A. (2016). Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets. Journal of Cleaner Production, 137, 213–229. https://doi.org/10.1016/j.jclepro.2016.07.031
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Atanassov, K. T. (1999). Intuitionistic fuzzy sets. In Intuitionistic fuzzy sets (pp. 1–137). Physica. https://doi.org/10.1007/978-3-7908-1870-3_1
Atanassov, K., & Gargov, G. (1989). Interval-valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 31(3), 343–349. https://doi.org/10.1016/0165-0114(89)90205-4
Banihashemi, S. A., Khalilzadeh, M., Antucheviciene, J., & Šaparauskas, J. (2021). Trading off time–cost–quality in construction project scheduling problems with fuzzy SWARA–TOPSIS approach. Buildings, 11(9), 387. https://doi.org/10.3390/buildings11090387
Bapat, H., Sarkar, D., & Gujar, R. (2021). Application of integrated fuzzy FCM-BIM-IoT for sustainable material selection and energy management of metro rail station box project in western India. Innovative Infrastructure Solutions, 6(2), 1–18. https://doi.org/10.1007/s41062-020-00431-7
Baušys, R., Juodagalvienė, B., Žiūrienė, R., Pankrašovaitė, I., Kamarauskas, J., Usovaitė, A., & Gaižauskas, D. (2020). The residence plot selection model for family house in Vilnius by neutrosophic WASPAS method. International Journal of Strategic Property Management, 24(3), 182–196. https://doi.org/10.3846/ijspm.2020.12107
Belošević, I., Kosijer, M., Ivić, M., & Pavlović, N. (2018). Group decision making process for early stage evaluations of IPs using extended VIKOR method under fuzzy environment. European Transport Research Review, 10(2), 1–14. https://doi.org/10.1186/s12544-018-0318-4
Bingham, E., & Gibson Jr, G. E. (2017). IP scope definition using project definition rating index. Journal of Management in Engineering, 33(2), 04016037. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000483
Bustince, H., & Burillo, P. (1996). Vague sets are intuitionistic fuzzy sets. Fuzzy Sets and Systems, 79(3), 403–405. https://doi.org/10.1016/0165-0114(95)00154-9
Büyüközkan, G., & Göçer, F. (2018). An extension of ARAS methodology under interval valued intuitionistic fuzzy environment for digital supply chain. Applied Soft Computing, 69, 634–654. https://doi.org/10.1016/j.asoc.2018.04.040
Chakraborty, S., & Zavadskas, E. K. (2014). Applications of WASPAS method in manufacturing decision making. Informatica, 25(1), 1–20. https://doi.org/10.15388/Informatica.2014.01
Chitsaz, N., & Banihabib, M. E. (2015). Comparison of different multi criteria decision-making models in prioritizing flood management alternatives. Water Resources Management, 29(8), 2503–2525. https://doi.org/10.1007/s11269-015-0954-6
Construction Industry Institute. (2010). Implementation Resource 268-2: Project Definition Rating Index—IPs. Austin, TX.
Davoudabadi, R., Mousavi, S. M., & Mohagheghi, V. (2020). A new last aggregation method of multi-attributes group decision making based on concepts of TODIM, WASPAS and TOPSIS under interval-valued intuitionistic fuzzy uncertainty. Knowledge and Information Systems, 62, 1371–1391. https://doi.org/10.1007/s10115-019-01390-x
Davoudabadi, R., Mousavi, S. M., & Mohagheghi, V. (2021). A new decision model based on DEA and simulation to evaluate renewable energy projects under interval-valued intuitionistic fuzzy uncertainty. Renewable Energy, 164, 1588–1601. https://doi.org/10.1016/j.renene.2020.09.089
Davoudabadi, R., Mousavi, S. M., Mohagheghi, V., & Vahdani, B. (2019). Resilient supplier selection through introducing a new interval-valued intuitionistic fuzzy evaluation and decision-making framework. Arabian Journal for Science and Engineering, 44(8), 7351–7360. https://doi.org/10.1007/s13369-019-03891-x
Dorfeshan, Y., & Mousavi, S. M. (2020). A novel interval type-2 fuzzy decision model based on two new versions of relative preference relation-based MABAC and WASPAS methods (with an application in aircraft maintenance planning). Neural Computing and Applications, 32(8), 3367–3385. https://doi.org/10.1007/s00521-019-04184-y
Egilmez, G., Gumus, S., Kucukvar, M., & Tatari, O. (2016). A fuzzy data envelopment analysis framework for dealing with uncertainty impacts of input–output life cycle assessment models on eco-efficiency assessment. Journal of Cleaner Production, 129, 622–636. https://doi.org/10.1016/j.jclepro.2016.03.111
Fouladgar, M. M., Yazdani-Chamzini, A., Lashgari, A., Zavadskas, E. K., & Turskis, Z. (2012). Maintenance strategy selection using AHP and COPRAS under fuzzy environment. International Journal of Strategic Property Management, 16(1), 85–104. https://doi.org/10.3846/1648715X.2012.666657
Gan, Q., & Hill, R. J. (2009). Measuring housing affordability: looking beyond the median. Journal of Housing Economics, 18(2), 115–125. https://doi.org/10.1016/j.jhe.2009.04.003
Gau, W. L., & Buehrer, D. J. (1993). Vague sets. IEEE Transactions on Systems, Man, and Cybernetics, 23(2), 610–614. https://doi.org/10.1109/21.229476
Gürbüz, T., Alptekin, S. E., & Alptekin, G. I. (2012). A hybrid MCDM methodology for ERP selection problem with interacting criteria. Decision Support Systems, 54(1), 206–214. https://doi.org/10.1016/j.dss.2012.05.006
Hajek, P., & Froelich, W. (2019). Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making. Information Sciences, 485, 394–412. https://doi.org/10.1016/j.ins.2019.02.035
Hashemi, H., Bazargan, J., & Mousavi, S. M. (2013). A compromise ratio method with an application to water resources management: an intuitionistic fuzzy set. Water Resources Management, 27, 2029–2051. https://doi.org/10.1007/s11269-013-0271-x
Jia, F., Liu, Y., & Wang, X. (2019). An extended MABAC method for multi-criteria group decision making based on intuitionistic fuzzy rough numbers. Expert Systems with Applications, 127, 241–255. https://doi.org/10.1016/j.eswa.2019.03.016
Karsak, E. E., & Dursun, M. (2015). An integrated fuzzy MCDM approach for supplier evaluation and selection. Computers & Industrial Engineering, 82, 82–93. https://doi.org/10.1016/j.cie.2015.01.019
Keshavarz Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Esmaeili, A. (2016). Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets. Journal of Cleaner Production, 137, 213–229. https://doi.org/10.1016/j.jclepro.2016.07.031
Mazher, K. M., Chan, A. P., Zahoor, H., Khan, M. I., & Ameyaw, E. E. (2018). Fuzzy integral–based risk-assessment approach for public–private partnership IPs. Journal of Construction Engineering and Management, 144(12), 04018111. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001573
Mishra, A. R., & Rani, P. (2018). Interval-valued intuitionistic fuzzy WASPAS method: application in reservoir flood control management policy. Group Decision and Negotiation, 27(6), 1047–1078. https://doi.org/10.1007/s10726-018-9593-7
Mohagheghi, V., Mousavi, S. M., Antuchevičienė, J., & Dorfeshan, Y. (2019). Sustainable infrastructure projects selection by a new group decision-making framework introducing MORAS method in an interval type 2 fuzzy environment. International Journal of Strategic Property Management, 23(6), 390–404. https://doi.org/10.3846/ijspm.2019.10536
Mulliner, E., Malys, N., & Maliene, V. (2016). Comparative analysis of MCDM methods for the assessment of sustainable housing affordability. Omega, 59, 146–156. https://doi.org/10.1016/j.omega.2015.05.013
Navarro, I. J., Penadés-Plà, V., Martínez-Muñoz, D., Rempling, R., & Yepes, V. (2020). Life cycle sustainability assessment for multi-criteria decision making in bridge design: a review. Journal of Civil Engineering and Management, 26(7), 690–704. https://doi.org/10.3846/jcem.2020.13599
Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016–3028. https://doi.org/10.1016/j.eswa.2014.11.057
Pires, A. S., Ferreira, F. A., Jalali, M. S., & Chang, H. C. (2018). Barriers to real estate investments for residential rental purposes: mapping out the problem. International Journal of Strategic Property Management, 22(3), 168–178. https://doi.org/10.3846/ijspm.2018.1541
Ranganath, N., Sarkar, D., Patel, P., & Patel, S. (2020). Application of fuzzy TOPSIS method for risk evaluation in development and implementation of solar park in India. International Journal of Construction Management, 1–11. https://doi.org/10.1080/15623599.2020.1826027
Roy, J., Ranjan, A., Debnath, A., & Kar, S. (2016). An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers. arXiv:1607.01254. https://arxiv.org/abs/1607.01254
Salimian, S., & Mousavi, S. M. (2021). A healthcare assessment for recycling hazardous waste by a new intuitionistic fuzzy decision method based on an assembled proportionate evaluation approach. Advances in Industrial Engineering, 55(3), 267–284. https://doi.org/10.22059/AIE.2021.328790.1798
Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231
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