A Systematic Comparative Review of Compromise Ranking Methods in Multi-Criteria Decision Making

Arkyadeep Sarkar; Shankha Shubhra Goswami; Dhiren Kumar Behera

doi:10.31181/sor202784

Authors

Arkyadeep Sarkar Department of Mechanical Engineering, Abacus Institute of Engineering and Management, Hooghly, India Author https://orcid.org/0000-0002-4597-4904
Shankha Shubhra Goswami Department of Mechanical Engineering, Abacus Institute of Engineering and Management, Hooghly, India Author https://orcid.org/0000-0002-0033-3089
Dhiren Kumar Behera Department of Mechanical Engineering, Indira Gandhi Institute of Technology, Sarang, India Author https://orcid.org/0000-0002-2547-5518

DOI:

https://doi.org/10.31181/sor202784

Keywords:

Multi-criteria decision-making (MCDM), Compromise ranking methods, VIKOR, TOPSIS, COPRAS, MOORA, MULTIMOORA, Bibliometric analysis, Sensitivity analysis, Hybrid intelligent systems

Abstract

MCDM has become a relevant framework for solving complex decision problems in which there are several conflicting criteria. Compromise ranking methods are one of the most important groups of methods in the MCDM family because they identify solutions that balance individual satisfaction and group utility while minimizing individual dissatisfaction and group regret. This study provides a systematic comparative study of the major compromise ranking methods, such as VIKOR, TOPSIS, COPRAS, MOORA, MULTIMOORA, and MOOSRA. The review is conducted using the PRISMA methodology and supplemented by bibliometric analysis in order to assess publication trends, prevailing subjects, the most popular journals, country representation, and emerging research areas. The study also investigates the methodological principles, normalization processes, computational complexity, robustness, sensitivity behaviour, ranking stability, and the capabilities of the methods to handle uncertainty. The results show that VIKOR is effective in providing explicit compromise solutions by balancing utility and regret, whereas MULTIMOORA is robust and shows superior ranking consistency because of its inherent multi-perspective structure. MOORA and MOOSRA are simpler methods that are computationally efficient and scalable for large-scale decision problems, whilst TOPSIS and COPRAS are intuitive and practical ranking methods. The review further reveals the expanding use of compromise ranking techniques in conjunction with fuzzy systems, artificial intelligence, machine learning, and real-time decision-support systems to address uncertainty and subjective weighting. Furthermore, the application analysis across engineering, energy, finance, healthcare, supply chain, sustainability, transportation, and intelligent systems demonstrates the wide range of applications of compromise ranking methods. In general, this research lays a solid groundwork for the future development of intelligent and adaptive MCDM systems.

Downloads

Download data is not yet available.

References

Ogrodnik, K. (2023). Application of MCDM/MCDA methods in city rankings-review and comparative analysis. Economics and Environment, 86(3), 132-151. https://doi.org/10.34659/eis.2023.86.3.689

Kizielewicz, B., Tomczyk, T., Gandor, M., & Sałabun, W. (2024). Subjective weight determination methods in multi-criteria decision-making: a systematic review. Procedia Computer Science, 246, 5396-5407. https://doi.org/10.1016/j.procs.2024.09.673

Kumar, R., & Pamucar, D. (2025). A comprehensive and systematic review of multi-criteria decision-making (MCDM) methods to solve decision-making problems: two decades from 2004 to 2024. Spectrum of Decision Making and Applications, 2(1), 177-196. https://doi.org/10.31181/sdmap21202524

Maral, M., & Özdemir, A. (2025). A systematic review on multi‐criteria decision‐making methods in educational research. British Educational Research Journal, 51(6), 3071-3106. https://doi.org/10.1002/berj.70002

Ayan, B., Abacıoğlu, S., & Basilio, M. P. (2023). A comprehensive review of the novel weighting methods for multi-criteria decision-making. Information, 14(5), 285. https://doi.org/10.3390/info14050285

Kpadé, C. P., Tamini, L. D., Pepin, S., Khasa, D. P., Abbas, Y., & Lamhamedi, M. S. (2024). Evaluating multi-criteria decision-making methods for sustainable management of forest ecosystems: A systematic review. Forests, 15(10), 1728. https://doi.org/10.3390/f15101728

Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple Attribute Decision Making (Lecture Notes in Economics and Mathematical Systems, Vol. 186, pp. 58-191). Springer. https://doi.org/10.1007/978-3-642-48318-9_3

Opricovic, S. (1990). Programski paket VIKOR za visekriterijumskokompromisno rangiranje. In Proceedings of the XVII Symposium on Operational Research SYM-OP-IS'1990, Kupari, Yugoslavia, October 9–12.

Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455. https://doi.org/10.1016/S0377-2217(03)00020-1

Opricovic, S., & Tzeng, G. H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2), 514-529. https://doi.org/10.1016/j.ejor.2006.01.020

Zavadskas, E. K., Kaklauskas, A., & Šarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 3, 131-139.

Zavadskas, E. K., & Turskis, Z. (2011). Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2), 397-427. https://doi.org/10.3846/20294913.2011.593291

Brauers, W. K., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 445-469.

Brauers, W. K. M., & Zavadskas, E. K. (2010). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24.

Das, M. C., Sarkar, B., & Ray, S. (2012). Decision making under conflicting environment: a new MCDM method. International Journal of Applied Decision Sciences, 5(2), 142-162. https://dx.doi.org/10.1504/IJADS.2012.046505

Taherdoost, H., & Madanchian, M. (2023). VIKOR Method—An Effective Compromising Ranking Technique for Decision Making. Macro Management & Public Policies, 5(2), 27–33. https://doi.org/10.30564/mmpp.v5i2.5578

Khosravi, A., & Ataei, M. (2026). A Comprehensive Review of Multi-Criteria Decision-Making Approaches in Mining Method Selection: Evolution, Trends, and Applications. Journal of Mining and Environment, 17(2), 763-780. https://doi.org/10.22044/jme.2025.16381.3193

Ismail, M. M., Abdelhady, H. R., & Emad, M. (2024). Multi-criteria decision-making techniques: a comprehensive review of methodologies and applications. International Journal of Computers and Informatics (Zagazig University), 2, 27-38. http://www.ijci.zu.edu.eg/index.php/ijci/article/view/70

Jong, F. C., & Ahmed, M. M. (2024). Multi-criteria decision-making solutions for optimal solar energy sites identification: a systematic review and analysis. IEEE Access, 12, 143458-143484. https://doi.org/10.1109/ACCESS.2024.3461948

Mukherjee, A. K., Gazi, K. H., Raisa, N., Momena, A. F., Mukherjee, S. B., Sobczak, A., Soheil, S., Prasad, M. S., & Ghosh, A. (2026). Review of alternative ranking methods in multi-criteria decision analysis based on WASPAS and CoCoSo methodologies. Yugoslav Journal of Operations Research. https://doi.org/10.2298/YJOR241215037M

Tian, G., Lu, W., Zhang, X., Zhan, M., Dulebenets, M. A., Aleksandrov, A., Fathollahi-Fard, A. M., & Ivanov, M. (2023). A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems. Environmental Science and Pollution Research, 30(20), 57279-57301. https://doi.org/10.1007/s11356-023-26577-2

Madanchian, M., & Taherdoost, H. (2025). Applications of multi-criteria decision making in information systems for strategic and operational decisions. Computers, 14(6), 208. https://doi.org/10.3390/computers14060208

Khan, N. A., Kumar, A., & Rao, N. (2025). An Insight into Multi-Criteria Decision Methods for the Selection of Robot: A Comprehensive Review. SN Computer Science, 6(6), 612. https://doi.org/10.1007/s42979-025-04143-6

Topaloğlu, F. (2024). Development of a new hybrid method for multi-criteria decision making (MCDM) approach: a case study for facility location selection. Operational Research, 24(4), 60. https://doi.org/10.1007/s12351-024-00871-4

Ferdous, J., Bensebaa, F., Milani, A. S., Hewage, K., Bhowmik, P., & Pelletier, N. (2024). Development of a generic decision tree for the integration of multi-criteria decision-making (MCDM) and multi-objective optimization (MOO) methods under uncertainty to facilitate sustainability assessment: a methodical review. Sustainability, 16(7), 2684. https://doi.org/10.3390/su16072684

Więckowski, J., Sałabun, W., Kizielewicz, B., Bączkiewicz, A., Shekhovtsov, A., Paradowski, B., & Wątróbski, J. (2023). Recent advances in multi-criteria decision analysis: A comprehensive review of applications and trends. International Journal of Knowledge-based and Intelligent Engineering Systems, 27(4), 367-393. https://doi.org/10.3233/KES-230487

Sipos, L., Galambosi, Z., Biró, P., Csató, L., & Bozóki, S. (2025). Trends and Directions of Preference Elicitation and Assessment in Food Science: Single‐, Pair‐, and Multi‐Criteria Ranking Methods. Food Science & Nutrition, 13(8), e70684. https://doi.org/10.1002/fsn3.70684

Al-Baldawi, Z. (2024). Assessment Lean Level in Manufacturing Enterprises Based on Fuzzy Multi-Criteria Decision Making (FMCDM) - Literature Review. International Journal of Supply and Operations Management, 11(1), 1-18. https://doi.org/10.22034/ijsom.2023.109817.2663

Chakraborty, S., Raut, R. D., Rofin, T. M., & Chakraborty, S. (2025). Supplier selection using multi-criteria decision making methods: a comprehensive review. OPSEARCH, 1-62. https://doi.org/10.1007/s12597-025-01009-6

Rishabh, R., & Das, K. N. (2025). A Critical Review on Metaheuristic Algorithms based Multi-Criteria Decision-Making Approaches and Applications. Archives of Computational Methods in Engineering, 32(2), 963-993. https://doi.org/10.1007/s11831-024-10165-9

Bajpai, S., & Chaturvedi, A. (2026). Evaluating multi-criteria decision making methods for influential nodes selection in social networks: A review. Multimedia Tools and Applications, 85(2), 79. https://doi.org/10.1007/s11042-026-21349-9

Liou, J. J., & Tzeng, G. H. (2012). Comments on "Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 18(4), 672-695. https://doi.org/10.3846/20294913.2012.753489

Mardani, A., Jusoh, A., Zavadskas, E. K., Cavallaro, F., & Khalifah, Z. (2015). Sustainable and renewable energy: An overview of the application of multiple criteria decision making techniques and approaches. Sustainability, 7(10), 13947-13984. https://doi.org/10.3390/su71013947

Aasa, O. P., Phoya, S., Monko, R. J., & Musonda, I. (2025). A theory-based decision support framework for energy transition: pluralized perspective. Frontiers in Sustainability, 6, 1703098. https://doi.org/10.3389/frsus.2025.1703098

Kandakoglu, A., Frini, A., & Ben Amor, S. (2019). Multicriteria decision making for sustainable development: A systematic review. Journal of Multi‐Criteria Decision Analysis, 26(5-6), 202-251. https://doi.org/10.1002/mcda.1682

Zahid, K., & Akram, M. (2023). Multi-criteria group decision-making for energy production from municipal solid waste in Iran based on spherical fuzzy sets. Granular Computing, 8(6), 1299-1323. https://doi.org/10.1007/s41066-023-00419-5

Hossain, M. S., Sikdar, M. S. H., Chowdhury, A., Bhuiyan, S. M. Y., & Mobin, S. M. (2025). AI-driven aggregate planning for sustainable supply chains: A systematic literature review of models, applications, and industry impacts. American Journal of Advanced Technology and Engineering Solutions, 1(01), 382-437. https://doi.org/10.63125/3jdpkd14

Safari, H., Faraji, Z., & Majidian, S. (2016). Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR. Journal of Intelligent Manufacturing, 27(2), 475-486. https://doi.org/10.1007/s10845-014-0880-0

Mardani, A., Zavadskas, E. K., Govindan, K., Amat Senin, A., & Jusoh, A. (2016). VIKOR technique: A systematic review of the state of the art literature on methodologies and applications. Sustainability, 8(1), 37. https://doi.org/10.3390/su8010037

Zenani, S., Obileke, K., Ndiweni, O., & Mukumba, P. (2025). A Review of the Application of Fuzzy Logic in Bioenergy Technology. Processes, 13(7), 2251. https://doi.org/10.3390/pr13072251

Mardani, A., Zavadskas, E. K., Khalifah, Z., Jusoh, A., & Nor, K. M. (2016). Multiple criteria decision-making techniques in transportation systems: A systematic review of the state of the art literature. Transport, 31(3), 359-385. https://doi.org/10.3846/16484142.2015.1121517

Yoon, K., & Hwang, C. L. (1985). Manufacturing plant location analysis by multiple attribute decision making: Part I—single-plant strategy. International Journal of Production Research, 23(2), 345-359. https://doi.org/10.1080/00207548508904712

Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289-301. https://doi.org/10.1016/j.ijpe.2005.03.009

Li, W., Yi, P., & Zhang, D. (2018). Sustainability evaluation of cities in northeastern China using dynamic TOPSIS-entropy methods. Sustainability, 10(12), 4542. https://doi.org/10.3390/su10124542

Wang, X., & Chan, H. K. (2013). A hierarchical fuzzy TOPSIS approach to assess improvement areas when implementing green supply chain initiatives. International Journal of Production Research, 51(10), 3117-3130. https://doi.org/10.1080/00207543.2012.754553

Ertay, T., Kahraman, C., & Kaya, İ. (2013). Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey. Technological and Economic Development of Economy, 19(1), 38-62. https://doi.org/10.3846/20294913.2012.762950

Lamrini, L., Abounaima, M. C., & Talibi Alaoui, M. (2023). New distributed-topsis approach for multi-criteria decision-making problems in a big data context. Journal of Big Data, 10(1), 97. https://doi.org/10.1186/s40537-023-00788-3

Elorduy, J. L., & Pino, Y. (2026). A Hybrid AHP–MCDM Model for Prioritising Accessibility Interventions in Urban Mobility Nodes: Application to Segovia (Spain). Urban Science, 10(1). https://doi.org/10.3390/urbansci10010053

Rogulj, K., Kilić Pamuković, J., Antucheviciene, J., & Zavadskas, E. K. (2022). Intuitionistic fuzzy decision support based on EDAS and grey relational degree for historic bridges reconstruction priority. Soft Computing, 26(18), 9419-9444. https://doi.org/10.1007/s00500-022-07259-6

Boonsothonsatit, G., Vongbunyong, S., Chonsawat, N., & Chanpuypetch, W. (2024). Development of a hybrid AHP-TOPSIS decision-making framework for technology selection in hospital medication dispensing processes. IEEE Access, 12, 2500-2516. https://doi.org/10.1109/ACCESS.2023.3348754

Xiang, Z., & Jianhua, H. (2026). Selecting an optimal alternative: a multi-criteria decision-making approach with cloud distance and prospect theory. Annals of Operations Research, 1-32. https://doi.org/10.1007/s10479-026-07094-0

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. https://doi.org/10.1016/j.asoc.2008.05.005

Zavadskas, E. K., Kaklauskas, A., Turskis, Z., & Tamošaitiene, J. (2008). Selection of the effective dwelling house walls by applying attributes values determined at intervals. Journal of Civil Engineering and Management, 14(2), 85-93. https://doi.org/10.3846/1392-3730.2008.14.3

Kanapeckiene, L., Kaklauskas, A., Zavadskas, E. K., & Seniut, M. (2010). Integrated knowledge management model and system for construction projects. Engineering Applications of Artificial Intelligence, 23(7), 1200-1215. https://doi.org/10.1016/j.engappai.2010.01.030

Valipour, A., Sarvari, H., & Tamošaitiene, J. (2018). Risk assessment in PPP projects by applying different MCDM methods and comparative results analysis. Administrative Sciences, 8(4), 80. https://doi.org/10.3390/admsci8040080

Rahim, M., Akhtar, Y., Yang, M. S., Ali, H. E., & Elhag, A. A. (2024). Improved COPRAS method with unknown weights under p, q-quasirung orthopair fuzzy environment: Application to green supplier selection. IEEE Access, 12, 69783-69795. https://doi.org/10.1109/ACCESS.2024.3400016

Yazdani, M., Pamucar, D., Chatterjee, P., & Torkayesh, A. E. (2022). A multi-tier sustainable food supplier selection model under uncertainty. Operations Management Research, 15(1), 116-145. https://doi.org/10.1007/s12063-021-00186-z

Brodny, J., Tutak, M., & Grebski, W. W. (2025). A holistic assessment of sustainable energy security and the efficiency of policy implementation in emerging EU economies: A long-term perspective. Energies, 18(7), 1767. https://doi.org/10.3390/en18071767

Roy, J., Das, S., Kar, S., & Pamučar, D. (2019). An extension of the CODAS approach using interval-valued intuitionistic fuzzy set for sustainable material selection in construction projects with incomplete weight information. Symmetry, 11(3), 393. https://doi.org/10.3390/sym11030393

Bączkiewicz, A., Kizielewicz, B., Shekhovtsov, A., Wątróbski, J., & Sałabun, W. (2021). Methodical aspects of MCDM based E-commerce recommender system. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2192-2229. https://doi.org/10.3390/jtaer16060122

Ecer, F. (2014). A hybrid banking websites quality evaluation model using AHP and COPRAS-G: a Turkey case. Technological and Economic Development of Economy, 20(4), 758-782. https://doi.org/10.3846/20294913.2014.915596

Matić, B., Jovanović, S., Das, D. K., Zavadskas, E. K., Stević, Ž., Sremac, S., & Marinković, M. (2019). A new hybrid MCDM model: Sustainable supplier selection in a construction company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353

Goswami, S. S., & Behera, D. K. (2021). Solving material handling equipment selection problems in an industry with the help of entropy integrated COPRAS and ARAS MCDM techniques. Process Integration and Optimization for Sustainability, 5(4), 947-973. https://doi.org/10.1007/s41660-021-00192-5

Brauers, W. K., & Zavadskas, E. K. (2009). Robustness of the multi‐objective MOORA method with a test for the facilities sector. Technological and Economic Development of Economy, 15(2), 352-375. https://doi.org/10.3846/1392-8619.2009.15.352-375

Chakraborty, S., Datta, H. N., Kalita, K., & Chakraborty, S. (2023). A narrative review of multi-objective optimization on the basis of ratio analysis (MOORA) method in decision making. Opsearch, 60(4), 1844-1887. https://doi.org/10.1007/s12597-023-00676-7

Brauers, W. K. M., Ginevičius, R., & Podvezko, V. (2010). Regional development in Lithuania considering multiple objectives by the MOORA method. Technological and Economic Development of Economy, 16(4), 613-640. https://doi.org/10.3846/tede.2010.38

Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). Personnel selection based on computing with words and fuzzy MULTIMOORA. Expert Systems with Applications, 39(9), 7961-7967. https://doi.org/10.1016/j.eswa.2012.01.100

Sen, D. K., Datta, S., Patel, S. K., & Mahapatra, S. S. (2017). Green supplier selection in fuzzy context: a decision-making scenario on application of fuzzy-MULTIMOORA. International Journal of Services and Operations Management, 28(1), 98-140. https://doi.org/10.1504/IJSOM.2017.085907

Brauers, W. K. M. (2013). Multi-objective seaport planning by MOORA decision making. Annals of Operations Research, 206(1), 39-58. https://doi.org/10.1007/s10479-013-1314-7

Balezentiene, L., Streimikiene, D., & Balezentis, T. (2013). Fuzzy decision support methodology for sustainable energy crop selection. Renewable and Sustainable Energy Reviews, 17, 83-93. https://doi.org/10.1016/j.rser.2012.09.016

Ulutaş, A., Stanujkic, D., Karabasevic, D., Popovic, G., Zavadskas, E. K., Smarandache, F., & Brauers, W. K. (2021). Developing of a novel integrated MCDM MULTIMOOSRAL approach for supplier selection. Informatica, 32(1), 145-161. https://doi.org/10.15388/21-INFOR445

Brauers, W. K. M., & Ginevičius, R. (2009). Robustness in regional development studies. The case of Lithuania. Journal of Business Economics and Management, 10(2), 121-140. https://doi.org/10.3846/1611-1699.2009.10.121-140

Turskis, Z., Zavadskas, E. K., & Peldschus, F. (2009). Multi-criteria optimization system for decision making in construction design and management. Engineering Economics, 61(1). https://doi.org/10.5755/j01.ee.61.1.11571

Singh, R., Pathak, V. K., Kumar, R., Dikshit, M., Aherwar, A., Singh, V., & Singh, T. (2024). A historical review and analysis on MOORA and its fuzzy extensions for different applications. Heliyon, 10(3). https://doi.org/10.1016/j.heliyon.2024.e25453

Chakhrit, A., Benharkat, N. E. H., Guetarni, I. H. M., Guedri, A., & Chennoufi, M. (2025). A literature review of risk assessment approaches in failure mode and effects analysis. International Journal of Quality & Reliability Management, 42(9), 2415-2454. https://doi.org/10.1108/IJQRM-01-2025-0042

Saboor, S., Ahmed, V., Anane, C., & Bahroun, Z. (2025). A hybrid AHP–Fuzzy MOORA decision support tool for advancing social sustainability in the construction sector. Sustainability, 17(11), 4879. https://doi.org/10.3390/su17114879

Hafezalkotob, A., & Hafezalkotob, A. (2016a). Fuzzy entropy-weighted MULTIMOORA method for materials selection. Journal of Intelligent & Fuzzy Systems, 31(3), 1211-1226. https://doi.org/10.3233/IFS-162186

Shamsipour, R., Nohegar, A., Ehsani, A. H., & Daryabeigi Zand, A. (2025). A comprehensive assessing of renewable energy sources ranking by fuzzy DANP and fuzzy MULTIMOORA (Case study Isfahan Province, IRAN). International Journal of Environmental Research, 19(4), 137. https://doi.org/10.1007/s41742-025-00763-1

Hafezalkotob, A., & Hafezalkotob, A. (2016b). Extended MULTIMOORA method based on Shannon entropy weight for materials selection. Journal of Industrial Engineering International, 12(1), 1-13. https://doi.org/10.1007/s40092-015-0123-9

Nguyen, N. A. T., Wang, C. N., Dang, L. T. H., Dang, L. T. T., & Dang, T. T. (2022). Selection of cold chain logistics service providers based on a grey AHP and grey COPRAS framework: a case study in Vietnam. Axioms, 11(4), 154. https://doi.org/10.3390/axioms11040154

Miç, P., & Antmen, Z. F. (2021). A decision-making model based on TOPSIS, WASPAS, and MULTIMOORA methods for university location selection problem. Sage Open, 11(3). https://doi.org/10.1177/21582440211040115

Murat, D., & Güzel, S. (2022). Determining the Inclusive Development Performances of the BRICS Countries and Turkey with MULTIMOORA. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 17(2), 535-560.

Kracka, M., & Zavadskas, E. K. (2013). Panel building refurbishment elements effective selection by applying multiple-criteria methods. International Journal of Strategic Property Management, 17(2), 210-219. https://doi.org/10.3846/1648715X.2013.808283

Baležentis, T., & Baležentis, A. (2014). A survey on development and applications of the multi‐criteria decision making method MULTIMOORA. Journal of Multi‐Criteria Decision Analysis, 21(3-4), 209-222. https://doi.org/10.1002/mcda.1501

Sampathkumar, S., Augustin, F., Kaabar, M. K., & Yue, X. G. (2023). An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection. Advances in Mechanical Engineering, 15(3). https://doi.org/10.1177/16878132231160265

Zavadskas, E. K., Bausys, R., Lescauskiene, I., & Usovaite, A. (2020). MULTIMOORA under interval-valued neutrosophic sets as the basis for the quantitative heuristic evaluation methodology HEBIN. Mathematics, 9(1), 66. https://doi.org/10.3390/math9010066

Tavana, M., Shaabani, A., Santos-Arteaga, F. J., & Valaei, N. (2021). An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics. Environmental Science and Pollution Research, 28(38), 53953-53982. https://doi.org/10.1007/s11356-021-14302-w

Soni, A., Das, P. K., & Sarma, M. (2022). Application of MOORA method for parametric optimization of manufacturing process of floor tiles using waste plastics. Process Integration and Optimization for Sustainability, 6(1), 113-123. https://doi.org/10.1007/s41660-021-00205-3

Sarkar, A., Panja, S. C., Das, D., & Sarkar, B. (2015). Developing an efficient decision support system for non-traditional machine selection: an application of MOORA and MOOSRA. Production & Manufacturing Research, 3(1), 324-342. https://doi.org/10.1080/21693277.2014.895688

Vasić, N., Kilibarda, M., & Andrejić, M. (2024). Selecting the e-commerce distribution channel by applying the integrated FAHP and MOOSRA methods. International Journal of Shipping and Transport Logistics, 18(3), 281-304. https://doi.org/10.1504/IJSTL.2024.139067

Narayanamoorthy, S., Annapoorani, V., Kang, D., Baleanu, D., Jeon, J., Kureethara, J. V., & Ramya, L. (2020). A novel assessment of bio-medical waste disposal methods using integrating weighting approach and hesitant fuzzy MOOSRA. Journal of Cleaner Production, 275, 122587. https://doi.org/10.1016/j.jclepro.2020.122587

Bhowmik, C., Dhar, S., & Ray, A. (2019). Comparative analysis of MCDM methods for the evaluation of optimum green energy sources: A case study. International Journal of Decision Support System Technology (IJDSST), 11(4), 1-28. https://doi.org/10.4018/IJDSST.2019100101

Kottala, S. Y. (2026). Fuzzy logic-based multi-criteria evaluation model for green supply chain decision support. International Journal of Productivity and Performance Management, 1-34. https://doi.org/10.1108/IJPPM-04-2025-0282

Sharaf, I. M., Albahri, O. S., Alsalem, M. A., Alamoodi, A. H., & Albahri, A. S. (2024). A novel dual-level multi-source information fusion approach for multicriteria decision making applications. Applied Intelligence, 54(22), 11577-11602. https://doi.org/10.1007/s10489-024-05624-6

Feizi, F., Karbalaei-Ramezanali, A. A., & Farhadi, S. (2021). FUCOM-MOORA and FUCOM-MOOSRA: new MCDM-based knowledge-driven procedures for mineral potential mapping in greenfields. SN Applied Sciences, 3(3), 358. https://doi.org/10.1007/s42452-021-04342-9

Barzegari, M. J., Mousavi, S. M., & Karami, S. (2023). An interval-valued fuzzy MULTIMOOSRAL method for supplier evaluation in oil production projects. Journal of Quality Engineering and Production Optimization, 8(1), 217-241. https://doi.org/10.22070/jqepo.2024.19451.1282

Stanujkic, D., Karabasevic, D., Zavadskas, E. K., Smarandache, F., & Brauers, W. K. (2019). A bipolar fuzzy extension of the MULTIMOORA method. Informatica, 30(1), 135-152. https://doi.org/10.3233/INF-2019-1215

Debbarma, S., Chakraborty, S., & Saha, A. K. (2025). Novel Fermatean fuzzy score function enriched decision support framework for biomedical waste recycling. Sādhanā, 50(4), 328. https://doi.org/10.1007/s12046-025-02964-y

Alhassan, S., Adamu, A. A., & Jimoh, M. T. (2026). Multi-criteria decision analysis and optimization approaches in sustainable waste-to-energy planning: A systematic review. FUDMA Journal of Engineering and Technology, 2(1), 108-123.

Chakraborty, S., Raut, R. D., Rofin, T. M., & Chakraborty, S. (2025). A comprehensive review on applications of multi-criteria decision-making methods in healthcare waste management. Waste Management & Research, 43(9), 1335-1357. https://doi.org/10.1177/0734242X251320872

Kamber, E., Yücel, B., & Gümüş, M. (2025). A review on multi-criteria decision-making in passenger transportation: Trends, methods, and future directions. Socio-Economic Planning Sciences, 102384. https://doi.org/10.1016/j.seps.2025.102384

Hagag, A. M., Yousef, L. S., & Abdelmaguid, T. F. (2023). Multi-criteria decision-making for machine selection in manufacturing and construction: Recent trends. Mathematics, 11(3), 631. https://doi.org/10.3390/math11030631

David, D., Albahri, O. S., Alamoodi, A. H., Albahri, A. S., Deveci, M., & Sharaf, I. M. (2025). Integrating Sensors and Multi-Criteria Decision Making (MCDM) in Precision Agriculture: A Mini Review. IEEE Sensors Reviews. https://doi.org/10.1109/SR.2025.3596890

Rai, D., Jha, G. K., Chatterjee, P., & Chakraborty, S. (2013). Material selection in manufacturing environment using compromise ranking and regret theory-based compromise ranking methods: A comparative study. Universal Journal of Materials Science, 1(2), 69-77.

Chakraborty, S., Datta, H. N., Kalita, K., & Chakraborty, S. (2023). A narrative review of multi-objective optimization on the basis of ratio analysis (MOORA) method in decision making. Opsearch, 60(4), 1844-1887. https://doi.org/10.1007/s12597-023-00676-7

Şahin, M. (2024). Ensemble multi-attribute decision-making for material selection problems. Soft Computing, 28(6), 5437-5460. https://doi.org/10.1007/s00500-023-09296-1

Vats, G., & Vaish, R. (2013). Piezoelectric material selection for transducers under fuzzy environment. Journal of Advanced Ceramics, 2(2), 141-148. https://doi.org/10.1007/s40145-013-0053-1

Girubha, R. J., & Vinodh, S. (2012). Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Materials & Design, 37, 478-486. https://doi.org/10.1016/j.matdes.2012.01.022

Siddiqui, Z. A., & Haroon, M. (2024). Ranking of components for reliability estimation of CBSS: an application of entropy weight fuzzy comprehensive evaluation model. International Journal of System Assurance Engineering and Management, 15(6), 2438-2452. https://doi.org/10.1007/s13198-024-02263-5

Peng, J. P., Yeh, W. C., Lai, T. C., & Hsu, C. B. (2015). The incorporation of the Taguchi and the VIKOR methods to optimize multi-response problems in intuitionistic fuzzy environments. Journal of the Chinese Institute of Engineers, 38(7), 897-907. https://doi.org/10.1080/02533839.2015.1037994

Mohamadghasemi, A., Hadi-Vencheh, A., Lotfi, F. H., & Khalilzadeh, M. (2020). An integrated group FWA-ELECTRE III approach based on interval type-2 fuzzy sets for solving the MCDM problems using limit distance mean. Complex & Intelligent Systems, 6(2), 355-389. https://doi.org/10.1007/s40747-020-00130-x

Datta, S., Sahu, N., & Mahapatra, S. (2013). Robot selection based on grey‐MULTIMOORA approach. Grey Systems: Theory and Application, 3(2), 201-232. https://doi.org/10.1108/GS-05-2013-0008

Salih, H. F. M., Ameen, Z. A., Alharbi, B., & Asaad, B. A. (2026). An integrated VIKOR–AHP method for green energy systems based on q-fractional hesitant fuzzy multi-criteria decision-making. Scientific Reports. https://doi.org/10.1038/s41598-026-46076-x

Rivero-Iglesias, J. M., Puente, J., Fernandez, I., & León, O. (2025). A Novel Combined Hybrid Group Multi-Criteria Decision-Making Model for the Selection of Power Generation Technologies. Systems, 13(9), 742. https://doi.org/10.3390/systems13090742

Sağbaş, A., Deveci, M., & Polat, U. (2023). A Decision Support System Based on Hybrid Approach With Copras And Interval Type-2 Fuzzy Topsis For Evaluation Of Renewable Energy Alternatives. European Journal of Engineering and Applied Sciences, 6(2), 61-73. https://doi.org/10.55581/ejeas.1392881

Baležentis, A., Baležentis, T., & Brauers, W. K. (2012). MULTIMOORA-FG: a multi-objective decision making method for linguistic reasoning with an application to personnel selection. Informatica, 23(2), 173-190. https://doi.org/10.3233/INF-2012-23(2)01

Wang, Q., & Zhou, K. (2017). A framework for evaluating global national energy security. Applied Energy, 188, 19-31. https://doi.org/10.1016/j.apenergy.2016.11.116

Büyüközkan, G., & Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000-3011. https://doi.org/10.1016/j.eswa.2011.08.162

Colapinto, C., Jayaraman, R., Ben Abdelaziz, F., & La Torre, D. (2020). Environmental sustainability and multifaceted development: multi-criteria decision models with applications. Annals of Operations Research, 293(2), 405-432. https://doi.org/10.1007/s10479-019-03403-y

Salas-Molina, F., Dutta, B., & Martínez, L. (2026). Strict Uncertainty Analysis with Fuzzy Payoffs and its Application to Portfolio Selection. Informatica, 1-28. https://doi.org/10.15388/26-INFOR625

Aouni, B., Doumpos, M., Pérez-Gladish, B., & Steuer, R. E. (2018). On the increasing importance of multiple criteria decision aid methods for portfolio selection. Journal of the Operational Research Society, 69(10), 1525-1542. https://doi.org/10.1080/01605682.2018.1475118

Dincer, H., & Hacioglu, U. (2015). A comparative performance evaluation on bipolar risks in emerging capital markets using fuzzy AHP-TOPSIS and VIKOR approaches. Engineering Economics, 26(2), 118-129. https://doi.org/10.5755/j01.ee.26.2.3591

Jana, S., Giri, B. C., Turskis, Z., Jana, C., & Hezam, I. M. (2025). Performance Measurement of Financial Officer Recruitment of a Company Using PIVN-AHP & PIVN-TOPSIS. Informatica, 36(4), 797-831. https://doi.org/10.15388/25-INFOR612

Baležentis, T., Misiūnas, A., & Baležentis, A. (2013). Efficiency and productivity change across the economic sectors in Lithuania (2000–2010): the DEA–MULTIMOORA approach. Technological and Economic Development of Economy, 19(sup1), S191-S213. https://doi.org/10.3846/20294913.2013.881431

Baydaş, M., Elma, O. E., & Pamučar, D. (2022). Exploring the specific capacity of different multi criteria decision making approaches under uncertainty using data from financial markets. Expert Systems with Applications, 197, 116755. https://doi.org/10.1016/j.eswa.2022.116755

Almasri, A., & Ying, M. (2024). Adopting circular economy principles: how do conflict management strategies help adopt smart technology in Jordanian SMEs? Sustainability, 16(21), 9475. https://doi.org/10.3390/su16219475

Modibbo, U. M., Hassan, M., Ahmed, A., & Ali, I. (2022). Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzy TOPSIS. Management Decision, 60(3), 806-836. https://doi.org/10.1108/MD-10-2020-1335

Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and Economic Development of Economy, 19(3), 533-548. https://doi.org/10.3846/20294913.2013.814606

Tozanli, O., Duman, G. M., Kongar, E., & Gupta, S. M. (2017). Environmentally concerned logistics operations in fuzzy environment: A literature survey. Logistics, 1(1), 4. https://doi.org/10.3390/logistics1010004

Singh, R. K., Gunasekaran, A., & Kumar, P. (2018). Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach. Annals of Operations Research, 267(1), 531-553. https://doi.org/10.1007/s10479-017-2591-3

Erdin, C., & Akbaş, H. E. (2019). A comparative analysis of fuzzy TOPSIS and geographic information systems (GIS) for the location selection of shopping malls: a case study from Turkey. Sustainability, 11(14), 3837. https://doi.org/10.3390/su11143837

Unanoglu, M. (2025). Evaluating Innovation, Quality of Life and Sustainability in OECD Countries: A Vikor Approach. Maliye ve Finans Yazıları, (Özel Sayı 3), 279-298. https://doi.org/10.33203/mfy.1830836

Ahvenniemi, H., & Huovila, A. (2021). How do cities promote urban sustainability and smartness? An evaluation of the city strategies of six largest Finnish cities. Environment, Development and Sustainability, 23(3), 4174-4200. https://doi.org/10.1007/s10668-020-00765-3

Aykut-Senel, B., Ates, N., Kaplan-Bekaroglu, S. S., & Ozgur, C. (2026). Comparative assessment of 2-methylisoborneol and geosmin removal techniques using multicriteria decision analysis. Integrated Environmental Assessment and Management. https://doi.org/10.1093/inteam/vjag049

Shahab, S., Simic, V., Dutta, A. K., Anjum, M., & Pamucar, D. (2026). Hybrid Pythagorean Fuzzy Decision-Making Framework for Sustainable Urban Planning under Uncertainty. Computer Modeling in Engineering & Sciences, 146(1). https://doi.org/10.32604/cmes.2025.073945

Te Boveldt, G., Keseru, I., & Macharis, C. (2021). How can multi-criteria analysis support deliberative spatial planning? A critical review of methods and participatory frameworks. Evaluation, 27(4), 492-509. https://doi.org/10.1177/13563890211020334

Foroozesh, F., Monavari, S. M., Salmanmahiny, A., Robati, M., & Rahimi, R. (2022). Assessment of sustainable urban development based on a hybrid decision-making approach: Group fuzzy BWM, AHP, and TOPSIS–GIS. Sustainable Cities and Society, 76, 103402. https://doi.org/10.1016/j.scs.2021.103402

Fu, X., & Wang, X. (2018). Developing an integrative urban resilience capacity index for plan making. Environment Systems and Decisions, 38(3), 367-378. https://doi.org/10.1007/s10669-018-9693-6

Özkurt, P. (2026). A Scenario-Robust Intuitionistic Fuzzy AHP–TOPSIS Model for Sustainable Healthcare Waste Treatment Selection: Evidence from Türkiye. Sustainability, 18(3), 1167. https://doi.org/10.3390/su18031167

Durur, F., & Akbulut, Y. (2026). The impact of quality on efficiency in training and research hospitals in Türkiye: data envelopment and panel regression analysis. Journal of Health Organization and Management, 1-16. https://doi.org/10.1108/JHOM-02-2025-0108

Büyüközkan, G., & Göçer, F. (2019). Smart medical device selection based on intuitionistic fuzzy Choquet integral. Soft Computing, 23(20), 10085-10103. https://doi.org/10.1007/s00500-018-3563-5

Lei, W. (2026). Decision support framework for prioritizing labor protection measures to enhance workplace safety and compliance in Industry 4.0 environments. Frontiers in Public Health, 14, 1781020. https://doi.org/10.3389/fpubh.2026.1781020

Pamucar, D., Torkayesh, A. E., & Biswas, S. (2023). Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. Annals of Operations Research, 328(1), 977-1019. https://doi.org/10.1007/s10479-022-04529-2

Digkoglou, P., & Papathanasiou, J. (2025). Application of multiple criteria decision aiding in environmental policy-making processes. International Journal of Environmental Science and Technology, 22(8), 6967-6982. https://doi.org/10.1007/s13762-024-06101-w

Soltani, M., Aouag, H., & Mouss, M. D. (2020). An integrated framework using VSM, AHP and TOPSIS for simplifying the sustainability improvement process in a complex manufacturing process. Journal of Engineering, Design and Technology, 18(1), 211-229. https://doi.org/10.1108/JEDT-09-2018-0166

Ibrahim, M. M., Shaban, M., El-Karim, E. A., & Samy, A. (2026). A multi-model approach for optimizing drainage water reuse sustainability in arid and semi-arid regions: a case study of El-Salam Canal project in Egypt. Applied Water Science. https://doi.org/10.1007/s13201-026-02797-y

Ghisellini, P., Ncube, A., Rotolo, G., Vassillo, C., Kaiser, S., Passaro, R., & Ulgiati, S. (2023). Evaluating environmental and energy performance indicators of food systems, within circular economy and "farm to fork" frameworks. Energies, 16(4), 1671. https://doi.org/10.3390/en16041671

Kim, Y., & Chung, E. S. (2013). Assessing climate change vulnerability with group multi-criteria decision making approaches. Climatic Change, 121(2), 301-315. https://doi.org/10.1007/s10584-013-0879-0

Garg, S. K., Versteeg, S., & Buyya, R. (2013). A framework for ranking of cloud computing services. Future Generation Computer Systems, 29(4), 1012-1023. https://doi.org/10.1016/j.future.2012.06.006

Maček, D., Magdalenić, I., & Ređep, N. B. (2020). A systematic literature review on the application of multicriteria decision making methods for information security risk assessment. International Journal of Safety and Security Engineering, 10(2), 161-174. https://doi.org/10.18280/ijsse.100202

Lanfranchi, G., Crupi, A., & Cesaroni, F. (2025). Internet of Things (IoT) and the Environmental Sustainability: A Literature Review and Recommendations for Future Research. Corporate Social Responsibility and Environmental Management, 32(6), 7648-7670. https://doi.org/10.1002/csr.70098

Cortinas-Lorenzo, K., Cai, W., & Doherty, G. (2025). Designing, implementing, and evaluating AI explanations: a scoping review of explainable AI frameworks. ACM Transactions on Computer-Human Interaction, 32(6), 1-79. https://doi.org/10.1145/3769678

Uzoka, F. M. E., Akinnuwesi, B. A., Oluwole, N., Adekoya, A. F., & Egbekunle, O. Y. (2016). Identifying factors for evaluating software project proposals. International Journal of Quality Engineering and Technology, 6(1-2), 93-114. https://doi.org/10.1504/IJQET.2016.081615

Ding, G. K. (2008). Sustainable construction—The role of environmental assessment tools. Journal of Environmental Management, 86(3), 451-464. https://doi.org/10.1016/j.jenvman.2006.12.025

Pasi, B. N., Dhamak, P. S., Todkari, V. C., & Kaldate, A. P. (2026). Artificial emotional intelligence for project management: A VIKOR-based prioritization of human-centric enablers and adoption strategies. International Journal of Managing Projects in Business, 1-31. https://doi.org/10.1108/IJMPB-10-2025-0454

Al-Shihabi, S., Piya, S., & Almurshidi, H. (2026). Sustainability and technical assessment of oil storage techniques using a hybrid Fuzzy AHP-VIKOR approach. Frontiers in Sustainability, 7, 1800181. https://doi.org/10.3389/frsus.2026.1800181

Atoum, I., Otoom, A. A., Baklizi, M., & Alkomah, F. (2026). Hybrid Fuzzy MCDM for Process-Aware Optimization of Agile Scaling in Industrial Software Projects. Processes, 14(2), 232. https://doi.org/10.3390/pr14020232

Castelnovo, W., Misuraca, G., & Savoldelli, A. (2016). Smart cities governance: The need for a holistic approach to assessing urban participatory policy making. Social Science Computer Review, 34(6), 724-739. https://doi.org/10.1177/0894439315611103

Rocha, C. M. M., Ospino, M. D., Ramos, I. B., & Guzman, A. M. (2024). Enhancing sustainable mobility: multi-criteria analysis for electric vehicle integration and policy implementation. International Journal of Energy Economics and Policy, 14(1), 205-218. https://doi.org/10.32479/ijeep.15021

Martinez, L., Keserü, I., & Macharis, C. (2026). Sustainable transport governance: Exploring the use of participatory multi-criteria analysis for planning inclusive infrastructure. Research in Transportation Economics, 116, 101730. https://doi.org/10.1016/j.retrec.2026.101730

Wanke, P., Tan, Y., & Floros, C. (2026). Do AI Markets Drive Financial Performance in Chinese Banks? A Quantum-Inspired (QI) MCDM Approach. Information Systems Frontiers, 1-19. https://doi.org/10.1007/s10796-025-10685-0

Le, Y., Alam, M. M., & Shafieezadeh, M. M. (2025). Prioritization of autonomous marine vehicle communication technologies using the VIKOR. Applied Water Science, 15(12), 296. https://doi.org/10.1007/s13201-025-02652-6

Saeidi, S., Jovanović, A., Kaisar, E., & Teodorović, D. (2026). Multiobjective Optimization of Signal Timings at a Displaced Left Turn: A Swarm Intelligence Approach. Journal of Transportation Engineering, Part A: Systems, 152(6), 04026033. https://doi.org/10.1061/JTEPBS.TEENG-9427

Kumar, R. (2025). A comprehensive review of MCDM methods, applications, and emerging trends. Decision Making Advances, 3(1), 185-199. https://doi.org/10.31181/dma31202569

Agrawal, A., Pandey, A. K., Baz, A., Alhakami, H., Alhakami, W., Kumar, R., & Khan, R. A. (2020). Evaluating the security impact of healthcare Web applications through fuzzy based hybrid approach of multi-criteria decision-making analysis. IEEE Access, 8, 135770-135783. https://doi.org/10.1109/ACCESS.2020.3010729

Madhavi, S., Santhosh, N. C., Rajkumar, S., & Praveen, R. (2023). Pythagorean fuzzy sets-based vikor and topsis-based multi-criteria decision-making model for mitigating resource deletion attacks in wsns. Journal of Intelligent & Fuzzy Systems, 44(6), 9441-9459. https://doi.org/10.3233/JIFS-224141

Alenezi, M., Agrawal, A., Kumar, R., & Khan, R. A. (2020). Evaluating performance of Web application security through a fuzzy based hybrid multi-criteria decision-making approach: Design tactics perspective. IEEE Access, 8, 25543-25556. https://doi.org/10.1109/ACCESS.2020.2970784

Najafzadeh, M., & Yeganeh, A. (2025). AI-Driven Digital Twins in Industrialized Offsite Construction: A Systematic Review. Buildings, 15(17), 2997. https://doi.org/10.3390/buildings15172997

Attaallah, A., Al-Sulbi, K., Alasiry, A., Marzougui, M., Ansar, S. A., Agrawal, A., Ansari, T. J., & Khan, R. A. (2023). Fuzzy-based unified decision-making technique to evaluate security risks: A healthcare perspective. Mathematics, 11(11), 2554. https://doi.org/10.3390/math11112554

Moreno, J. J. S., Matoma, J. A. O., Castillo, M. R. D., & Sarchi, J. A. O. (2024). A neutrosophic framework for evaluating security measures in information systems. Journal of Fuzzy Extension and Applications, 5, 12-24. https://doi.org/10.22105/jfea.2024.468184.1546

Alosaimi, W., Alharbi, A., Alyami, H., Alouffi, B., Almulihi, A., Ahmad, M., Nadeem, M., & Khan, R. A. (2025). Decision analysis of IoT-based big data analytics in smart cities of Saudi Arabia. PeerJ Computer Science, 11, e3383. https://doi.org/10.7717/peerj-cs.3383

Almeida, R. P., Ayala, N. F., Benitez, G. B., Kliemann Neto, F. J., & Frank, A. G. (2023). How to assess investments in industry 4.0 technologies? A multiple-criteria framework for economic, financial, and sociotechnical factors. Production Planning & Control, 34(16), 1583-1602. https://doi.org/10.1080/09537287.2022.2035445