Share:


Evaluation of infrastructure projects by a decision model based on RPR, MABAC, and WASPAS methods with interval-valued intuitionistic fuzzy sets

    Sina Salimian Affiliation
    ; Seyed Meysam Mousavi Affiliation
    ; Jurgita Antuchevičienė   Affiliation

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
Published in Issue
Feb 22, 2022
Abstract Views
241
PDF Downloads
235
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Arshad, H., Thaheem, M. J., Bakhtawar, B., & Shrestha, A. (2021). Evaluation of road IPs: a life cycle sustainability-based decision-making approach. Sustainability, 13(7), 3743. https://doi.org/10.3390/su13073743

Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

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

Stević, Ž., Pamučar, D., Subotić, M., Antuchevičiene, J., & Zavadskas, E. K. (2018). The location selection for roundabout construction using Rough BWM-Rough WASPAS approach based on a new Rough Hamy aggregator. Sustainability, 10(8), 2817. https://doi.org/10.3390/su10082817

Su, L., & Li, H. (2021). Project procurement method decision-making with spearman rank correlation coefficient under uncertainty circumstances. International Journal of Decision Support System Technology (IJDSST), 13(2), 16–44. https://doi.org/10.4018/IJDSST.2021040102

Taillandier, F., Taillandier, P., Tepeli, E., Breysse, D., Mehdizadeh, R., & Khartabil, F. (2015). A multi-agent model to manage risks in construction project (SMACC). Automation in Construction, 58, 1–18. https://doi.org/10.1016/j.autcon.2015.06.005

Turskis, Z., Antuchevičienė, J., Keršulienė, V., & Gaidukas, G. (2019). Hybrid group MCDM model to select the most effective alternative of the second runway of the airport. Symmetry, 11(6), 792. https://doi.org/10.3390/sym11060792

Turskis, Z., Zavadskas, E. K., Antucheviciene, J., & Kosareva, N. (2015). A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection. International Journal of Computers Communications & Control, 10(6), 113–128. https://doi.org/10.15837/ijccc.2015.6.2078

Wang, Y. J. (2015). Ranking triangle and trapezoidal fuzzy numbers based on the relative preference relation. Applied Mathematical Modelling, 39(2), 586–599. https://doi.org/10.1016/j.apm.2014.06.011

Wu, Y., Geng, S., Xu, H., & Zhang, H. (2014). Study of decision framework of wind farm project plan selection under intuitionistic fuzzy set and fuzzy measure environment. Energy Conversion and Management, 87, 274–284. https://doi.org/10.1016/j.enconman.2014.07.001

Xu, Z. S., & Chen, J. (2007). Approach to group decision making based on interval-valued intuitionistic judgment matrices. Systems Engineering - Theory & Practice, 27(4), 126–133. https://doi.org/10.1016/S1874-8651(08)60026-5

Xue, Y. X., You, J. X., Lai, X. D., & Liu, H. C. (2016a). An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Applied Soft Computing, 38, 703–713. https://doi.org/10.1016/j.asoc.2015.10.010

Xue, Y. X., You, J. X., Zhao, X., & Liu, H. C. (2016b). An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information. International Journal of Production Research, 54(18), 5452–5467. https://doi.org/10.1080/00207543.2016.1146418

Yazdani, M., Alidoosti, A., & Zavadskas, E. K. (2011). Risk analysis of critical infrastructures using fuzzy COPRAS. Economic Research-Ekonomska Istraživanja, 24(4), 27–40. https://doi.org/10.1080/1331677X.2011.11517478

Yue, Z. (2012). Extension of TOPSIS to determine weight of decision maker for group decision making problems with uncertain information. Expert Systems with Applications, 39(7), 6343–6350. https://doi.org/10.1016/j.eswa.2011.12.016

Zavadskas, E. K., Antucheviciene, J., Razavi Hajiagha, S. H., & Hashemi, S. S. (2014). Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF). Applied Soft Computing, 24, 1013–1021. https://doi.org/10.1016/j.asoc.2014.08.031

Zavadskas, E. K., Kalibatas, D., & Kalibatiene, D. (2016). A multi-attribute assessment using WASPAS for choosing an optimal indoor environment. Archives of Civil and Mechanical Engineering, 16(1), 76–85. https://doi.org/10.1016/j.acme.2015.10.002

Zavadskas, E. K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika, 122(6), 3–6. https://doi.org/10.5755/j01.eee.122.6.1810

Zavadskas, E., Baušys, R., & Lazauskas, M. (2015). Sustainable assessment of alternative sites for the construction of a waste incineration plant by applying WASPAS method with single-valued neutrosophic set. Sustainability, 7(12), 15923–15936. https://doi.org/10.3390/su71215792

Zhang, L., Zhao, Z., & Kan, Z. (2019). Private‐sector partner selection for public‐private partnership projects of electric vehicle charging infrastructure. Energy Science & Engineering, 7(5), 1469–1484. https://doi.org/10.1002/ese3.367