In an era of rapid change, complexity, and uncertainty, organizations must rely on sustainable project portfolio management to achieve long-term objectives. In project-oriented environments, selecting the most suitable project portfolio remains a critical challenge. To address this, advanced decision-making approaches, particularly multi-criteria decision-making (MCDM) techniques, have been developed to support well-informed and dependable choices. This study develops a new synergistic integration of Interval-Valued Fuzzy Level-Based Weight Assessment (IVF-LBWA) and Interval-Valued Fuzzy Multi-Attribute Ideal Real Comparative Analysis (IVF-MAIRCA), to improve decision-making in uncertain environments. In contrast to traditional methods, these approaches utilize interval-valued fuzzy numbers, thereby increasing the precision of project ranking and selection. An application example involving five projects and six evaluation criteria is provided to demonstrate the practical application of these methods. The results indicate that IVF-LBWA and IVF-MAIRCA yield stable and consistent project rankings, reinforcing their applicability in real-world scenarios. A sensitivity analysis was performed across 40 different criteria weighting scenarios to evaluate the impact of weight variations on project rankings. The results demonstrate that the proposed integrated approach preserves ranking stability, reflecting decision-makers’ priorities and the relative importance of each criterion. These findings validate its effectiveness in managing uncertainty and supporting reliable decision-making. The findings confirm that this approach provides a systematic and reliable framework for sustainable project portfolio selection. By enhancing decision accuracy and strengthening resilience to uncertainty, it enables decision-makers to align project selection with long-term sustainability, resource efficiency, and strategic objectives.
Schoper, Y.-G., Wald, A., Ingason, H. T., & Fridgeirsson, T. V. (2018). Projectification in Western economies: A comparative study of Germany, Norway and Iceland. International Journal of Project Management, 36(1), 71–82.
Zahmatkesh, M. and Shakhsi-Niaei, M. (2023). Sustainable Project Portfolio Selection Considering Combined Rankings Under Uncertainty: A Case Study. Advances in Industrial Engineering, 57(2), 187-201.
Hatami-Marbini, A., Saati, S., & Sajadi, S. M. (2018). Efficiency analysis in two-stage structures using fuzzy data envelopment analysis. Central European Journal of Operations Research, 26(4), 909–932.
Lorincová, S., Štarchoň, P., Weberová, D., Hitka, M., & Lipoldová, M. (2019). Employee motivation as a tool to achieve sustainability of business processes. Sustainability, 11(13), 3509.
Kandakoglu, M., Walther, G., & Ben Amor, S. (2024). The use of multi-criteria decision-making methods in project portfolio selection: a literature review and future research directions. Annals of Operations Research, 332(1–3), 807–830.
Bouyari, F., Moussavi, S. M. and Vahdani, B. (2018). A Mathematical Model for Project Portfolio Selection with Project Interdependency, Project Divisibility, Reinvestment and Resourcing in Different Ways. Advances in Industrial Engineering, 52(2), 163-177.
Touni, Z., Makui, A. and Mohammadi, E. (2020). A More Human-Like Portfolio Optimization Approach: Using Utility Function to Find an Individualized Portfolio. Advances in Industrial Engineering, 54(3), 293-310.
Zhu, Q., Dou, Y., & Sarkis, J. (2010). A portfolio‐based analysis for green supplier management using the analytical network process. Supply Chain Management: An International Journal, 15(4), 306–319.
Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J.-P., & Pla-Rubio, A. (2014). An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects. Energy (Oxford, England), 66, 222–238.
Szilágyi, I., Sebestyén, Z., & Tóth, T. (2019). Project Ranking in Petroleum Exploration. The Engineering Economist, 65(1), 66–87.
Lee, H. Y., Heng, Y. P., Selvanathan, K., Chandrahasan, P., & Chemmangattuvalappil, N. G. (2024). Multi-criteria decision-making tools for project selection by international conglomerates. Process Integration and Optimization for Sustainability, 8(2), 375–393.
Alsanousi, A. T., Alqahtani, A. Y., Makki, A. A., & Baghdadi, M. A. (2024). A Hybrid MCDM Approach Using the BWM and the TOPSIS for a Financial Performance-Based Evaluation of Saudi Stocks. Information, 15(5), 258.
Khalili-Damghani, K., & Tavana, M. (2014). A comprehensive framework for sustainable project portfolio selection based on structural equation modeling. Project Management Journal, 45(2), 83–97.
Siew, R. Y. J. (2016). Integrating sustainability into construction project portfolio management. KSCE Journal of Civil Engineering, 20(1), 101–108.
RezaHoseini, A., Ghannadpour, S. F., & Hemmati, M. (2020). A comprehensive mathematical model for resource-constrained multi-objective project portfolio selection and scheduling considering sustainability and projects splitting. Journal of Cleaner Production, 269(122073), 122073.
Rahimi, F., Davari-Ardakani, H., Ameli, M., & Kabiri Beheshtkhah, M. (2024). Sustainable project selection and scheduling using scenario-based stochastic programming: a case study of industrial projects. Stochastic Environmental Research and Risk Assessment: Research Journal, 38(2), 593–619.
Parvaneh, F., & Hammad, A. (2024). Application of Multi-Criteria Decision-Making (MCDM) to Select the Most Sustainable Power-Generating Technology. Sustainability, 16(8), 3287.
Askari Lasaki, A., Adlparvar, M. R. and Shahbazi, M. S. (2021). An Integrated Soft Computing Method Based on Intuitionistic Fuzzy Environment to Appraise the Urban Bridge Maintenance Models. Advances in Industrial Engineering, 55(3), 307-322.
Salimian, S., & Mousavi, S. M. (2021). Healthcare waste disposal location selection by a multi-criteria decision-making method with intuitionistic fuzzy sets. Journal of Quality Engineering and Production Optimization, 6(2), 143-156.
Mohagheghi, V., Mousavi, S. M., & Siadat, A. (2015). A new approach in considering vagueness and lack of knowledge for selecting sustainable portfolio of production projects. 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 1732–1736.
Wu, Y., Xu, C., Ke, Y., Tao, Y., & Li, X. (2019). Portfolio optimization of renewable energy projects under type-2 fuzzy environment with sustainability perspective. Computers & Industrial Engineering, 133, 69–82.
Mohagheghi, V., & Mousavi, S. M. (2020). D-WASPAS: Addressing social cognition in uncertain decision-making with an application to a sustainable project portfolio problem. Cognitive Computation, 12(3), 619–641.
Ma, J., Harstvedt, J. D., Jaradat, R., & Smith, B. (2020). Sustainability driven multi-criteria project portfolio selection under uncertain decision-making environment. Computers & Industrial Engineering, 140(106236), 106236.
Jalilibal, Z., & Bozorgi-Amiri, A. (2022). A Hybrid Grounded Theory, Fuzzy DEMATEL and ISM Method for Assessment of Sustainability Criteria for Project Portfolio Selection Problems. Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies), 15(3), 425-442.
Mohagheghi, V., Mousavi, S. M., & Shahabi-Shahmiri, R. (2022). Sustainable project portfolio selection and optimization with considerations of outsourcing decisions, financing options and staff assignment under interval type-2 fuzzy uncertainty. Neural Computing & Applications, 34(17), 14577–14598.
Huang, Y. Y., Pan, J., Tsaur, R. C., & Lin, N. C. (2024). Fuzzy portfolio selection in the trade-off between different economy trends and security returns. Applied Mathematics in Science and Engineering, 33(1).
Vasantha Lakshmi, K., & Udaya Kumara, K. N. (2024). A novel randomized weighted fuzzy AHP by using modified normalization with the TOPSIS for optimal stock portfolio selection model integrated with an effective sensitive analysis. Expert Systems with Applications, 243(122770), 122770.
Jawad, M., Naz, M., & Muqaddus, H. (2024). A multi-criteria decision-making approach for portfolio selection by using an automatic spherical fuzzy AHP algorithm. The Journal of the Operational Research Society, 75(1), 85–98.
Vasantha Lakshmi, K., & Udaya Kumara, K. N. (2025). Fuzzy MCDM techniques for portfolio selection in the post-COVID Indian mutual fund market: a comparative study of FAHP and entropy methods. Journal of Ambient Intelligence and Humanized Computing, 16(1), 97-107.
Sharma, S. K. (2025). Enhancing Stock Portfolio Selection with Trapezoidal Bipolar Fuzzy VIKOR Technique with Boruta-GA Hybrid Optimization Model: A Multicriteria Decision-Making Approach. International Journal of Computational Intelligence Systems, 18(1), 17.
Žižović, M., Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia, Pamučar, D., & Department of logistics, Military academy, University of defence, Serbia. (2019). New model for determining criteria weights: Level Based Weight Assessment (LBWA) model. Decision Making Applications in Management and Engineering, 2(2).
Pamucar, D., Deveci, M., Canıtez, F., & Lukovac, V. (2020). Selecting an airport ground access mode using novel fuzzy LBWA-WASPAS-H decision making model. Engineering Applications of Artificial Intelligence, 93(103703), 103703.
Božanić, D., Ranđelović, A., Radovanović, M., & Tešić, D. (2020). A hybrid lbwa - Ir-mairca multi-criteria decision-making model for determination of constructive elements of weapons. Facta Universitatis Series Mechanical Engineering, 18(3), 399.
Torkayesh, A. E., Pamucar, D., Ecer, F., & Chatterjee, P. (2021). An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe. Socio-Economic Planning Sciences, 78(101052), 101052.
Jokić, Ž., Božanić, D., Pamučar, D. (2021). Selection of fire position of mortar units using lbwa and fuzzy mabac model. Operational Research in Engineering Sciences: Theory and Applications, 4(1).
Pamucar, D., & Faruk Görçün, Ö. (2022). Evaluation of the European container ports using a new hybrid fuzzy LBWA-CoCoSo’B techniques. Expert Systems with Applications, 203(117463), 117463.
Ögel, İ. Y., Ecer, F., & Özgöz, A. A. (2023). Identifying the leading retailer-based food waste causes in different perishable fast-moving consumer goods’ categories: application of the F-LBWA methodology. Environmental Science and Pollution Research International, 30(12), 32656–32672.
Božanić, D., Pamucar, D., Badi, I., & Tešić, D. (2023). A decision support tool for oil spill response strategy selection: application of LBWA and Z MABAC methods. Quarterly Journal of the Operational Research Society of India, 60(1), 24–58.
Ogundoyin, S. O., & Kamil, I. A. (2023). An integrated Fuzzy-BWM, Fuzzy-LBWA and V-Fuzzy-CoCoSo-LD model for gateway selection in fog-bolstered Internet of Things. Applied Soft Computing, 143(110393), 110393.
Özekenci, E. K. (2024). Personnel selection based on the LBWA, TOPSIS and GRA methods: A case study on foreign trade company. Fiscaoeconomia, 8(2), 646–665.
Pamučar, D., Vasin, L., & Lukovac, V. (2014). Selection of railway level crossings for investing in security equipment using hybrid dematel-maric model: Application of a new method of multi-criteria decision-making.
Boral, S., Howard, I., Chaturvedi, S. K., McKee, K., & Naikan, V. N. A. (2020). A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing. Sustainable Production and Consumption, 21, 14–32.
Gul, M., & Ak, M. F. (2020). Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA. Stochastic Environmental Research and Risk Assessment: Research Journal, 34(8), 1231–1262.
Hadian, S., Shahiri Tabarestani, E., & Pham, Q. B. (2022). Multi attributive ideal-real comparative analysis (MAIRCA) method for evaluating flood susceptibility in a temperate Mediterranean climate. Journal Des Sciences Hydrologiques [Hydrological Sciences Journal], 67(3), 401–418.
Gul, M., Mete, S., Serin, F., & Celik, E. (2021). Fine–Kinney-based occupational risk assessment using fuzzy best and worst method (F-BWM) and fuzzy MAIRCA. In Fine–Kinney-Based Fuzzy Multi-Criteria Occupational Risk Assessment(pp. 13–30). Springer International Publishing.
Ecer, F. (2022). An extended MAIRCA method using intuitionistic fuzzy sets for coronavirus vaccine selection in the age of COVID-19. Neural Computing & Applications, 34(7), 5603–5623.
Nguyen, H.-Q., Nguyen, V.-T., Phan, D.-P., Tran, Q.-H., & Vu, N.-P. (2022). Multi-criteria decision making in the PMEDM process by using MARCOS, TOPSIS, and MAIRCA methods. Applied Sciences (Basel, Switzerland), 12(8), 3720.
Eti, S., & Baş, H. (2023). Determining the social exclusion levels of international students from different regions using the MAIRCA and TOPSIS method. Globalisation Societies and Education, 1–20.
Tepe, S., Eti, S., Moda, H. M., & Kahraman, Z. (2024). Evaluation of psychosocial risk factors encountered for energy sector employees by MAIRCA method. In Contributions to Management Science(pp. 65–83). Springer Nature Switzerland.
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information Sciences, 8(3), 199–249.
Zimmermann, H.-J. (1986). Fuzzy set theory and mathematical programming. In Fuzzy Sets Theory and Applications(pp. 99–114). Springer Netherlands.
Grattan-Guinness, I. (1976). Fuzzy membership mapped onto intervals and many-valued quantities. Mathematical Logic Quarterly, 22(1), 149–160.
Karnik, N., & M. Mendel, J. (2001). Operations on type-2 fuzzy sets. Fuzzy Sets and Systems. An International Journal in Information Science and Engineering, 122(2), 327–348.
Ashtiani, B., Haghighirad, F., Makui, A., & Montazer, G. A. (2009). Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Applied Soft Computing, 9(2), 457–461.
Vahdani, B., Hadipour, H., Sadaghiani, J. S., & Amiri, M. (2010). Extension of VIKOR method based on interval-valued fuzzy sets. The International Journal of Advanced Manufacturing Technology, 47(9–12), 1231–1239.
Gorzałczany, M. B. (1987). A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets and Systems. An International Journal in Information Science and Engineering, 21(1), 1–17.
Yao, J.-S., & Lin, F.-T. (2002). Constructing a fuzzy flow-shop sequencing model based on statistical data. International Journal of Approximate Reasoning: Official Publication of the North American Fuzzy Information Processing Society, 29(3), 215–234.
Chen, S.-M. (2002). Fuzzy system reliability analysis based on vague set theory. 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.
Hong, D. H., & Lee, S. (2002). Some algebraic properties and a distance measure for interval-valued fuzzy numbers. Information Sciences, 148(1–4), 1–10.
Chen, S.-J., & Chen, S.-M. (2008). Fuzzy risk analysis based on measures of similarity between interval-valued fuzzy numbers. Computers & Mathematics with Applications (Oxford, England: 1987), 55(8), 1670–1685.
Ashtiani, B., Haghighirad, F., Makui, A., & ali Montazer, G. (2009). Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Applied Soft Computing, 9(2), 457-461.
Dorfeshan, Y., Mousavi, S. M., Zavadskas, E. K., & Antucheviciene, J. (2021). A new enhanced ARAS method for critical path selection of engineering projects with interval type-2 fuzzy sets. International Journal of Information Technology & Decision Making, 20(01), 37-65.
Dorfeshan, Y., Jolai, F., & Mousavi, S. M. (2023). A multi-criteria decision-making model for analyzing a project-driven supply chain under interval type-2 fuzzy sets. Applied Soft Computing, 148, 110902.
Aramesh, S., Mousavi, S. M., & Mohagheghi, V. (2021). A new comprehensive project scheduling, monitoring, and management framework based on the critical chain under interval type-2 fuzzy uncertainty. Iranian Journal of Fuzzy Systems, 18(1), 151-170.
Karami, S. and Mousavi, S. M. (2025). An Interval-Valued Fuzzy Group Decision-Making Model Based on Two New Developed IVF-LBWA and IVF-MAIRCA Methods for Sustainable Project Selection. Advances in Industrial Engineering, 59(2), 279-305. doi: 10.22059/aie.2025.386811.1929
MLA
Karami, S. , and Mousavi, S. M. . "An Interval-Valued Fuzzy Group Decision-Making Model Based on Two New Developed IVF-LBWA and IVF-MAIRCA Methods for Sustainable Project Selection", Advances in Industrial Engineering, 59, 2, 2025, 279-305. doi: 10.22059/aie.2025.386811.1929
HARVARD
Karami, S., Mousavi, S. M. (2025). 'An Interval-Valued Fuzzy Group Decision-Making Model Based on Two New Developed IVF-LBWA and IVF-MAIRCA Methods for Sustainable Project Selection', Advances in Industrial Engineering, 59(2), pp. 279-305. doi: 10.22059/aie.2025.386811.1929
CHICAGO
S. Karami and S. M. Mousavi, "An Interval-Valued Fuzzy Group Decision-Making Model Based on Two New Developed IVF-LBWA and IVF-MAIRCA Methods for Sustainable Project Selection," Advances in Industrial Engineering, 59 2 (2025): 279-305, doi: 10.22059/aie.2025.386811.1929
VANCOUVER
Karami, S., Mousavi, S. M. An Interval-Valued Fuzzy Group Decision-Making Model Based on Two New Developed IVF-LBWA and IVF-MAIRCA Methods for Sustainable Project Selection. Advances in Industrial Engineering, 2025; 59(2): 279-305. doi: 10.22059/aie.2025.386811.1929