[1] V. Villani, A. Scuderi, G.S. Ponticelli, S. Guarino, Enhanced mechanical performance of laser sintered lattice structures: insights from experimental testing and finite element analysis. Progress in Additive Manufacturing, 10, 2025: 8707-8727. https://doi.org/10.1007/s40964-025-01150-0
[2] V. Tagliaferri, F. Trovalusci, S. Guarino, S. Venettacci, Environmental and Economic Analysis of FDM, SLS and MJF Additive Manufacturing Technologies. Materials, 12(24), 2019: 4161.
https://doi.org/10.3390/ma12244161
[3] C. Divya, L. S. Raju, B. Singaravel, Application of MCDM Methods for Process Parameter Optimization in Turning Process—A Review. Lecture Notes in Mechanical Engineering, 2021: 199-207.
https://doi.org/10.1007/978-981-15-7557-0_18
[4] T.V. Dua, H.X. Thinh, N.C. Bao, D.V. Duc, T.M. Hoang, Multi-Objective Optimization of the Turning Process using the Probability Method. Engineering, Technology & Applied Science Research, 15(1), 2025: 19865-19870. https://doi.org/10.48084/etasr.9472
[5] H.L.H. Yen, H.Q. Minh, T.T. Nhuan, N.T.H. Quynh, Áp dụng các phương pháp ra quyết định đa tiêu chí để xác định nồng độ ethanol chiết xuất loài xoan leo. Journal of Science and Technology – HaUI, 61(5B), 2025: 438-444. (in Vietnamese) https://doi.org/10.57001/huih5804.2025.202
[6] D. Lukic, M. Milosevic, A. Antic, S. Borojevic, M. Ficko, Multi‐criteria selection of manufacturing processes in the conceptual process planning. Advances in Production Engineering & Management, 12(2), 2017: 151-162. https://doi.org/10.14743/apem2017.2.247
[7] Z. Yang, P. Liu, X. Fang, G. Chen, The Selection of Storage Period for Fresh Rice Noodles, Processing Materials, and the Screening of Key Indicators. Foods, 13(23), 2024: 3965.
https://doi.org/10.3390/foods13233965
[8] M.M. Farag, Materials and process selection for engineering design. CRC Press, 2013.
https://doi.org/10.1201/b16047
[9] M. Urgo, G. Lanza, R. Vrabič, D. Gyulai, Future-Proof Production Scheduling and Control. CIRP Annals, 74(2), 2025: 971-991. https://doi.org/10.1016/j.cirp.2025.04.095
[10] A. Presciuttini, A. Portioli-Staudacher, Applications of IoT and Advanced Analytics for manufacturing operations: a systematic literature review. Procedia Computer Science, 232, 2024: 327-336.
https://doi.org/10.1016/j.procs.2024.01.032
[11] R. Aaij, L. Anderlini, S. Benson, M. Cattaneo, P. Charpentier, M. Clemencic, A. Falabella, F. Ferrari, M. Fontana, V. V. Gligorov, D. Hill, T. Humair, C. R. Jones, O. Lupton, S. Malde, C. M. Benito, R. Matev, A. Pearce, A. Poluektov, B. Sciascia, F. Stagni, R. V. Gomez, Y. Zhang, Selection and processing of calibration samples to measure the particle identification performance of the LHCb experiment in Run 2. EPJ Techniques and Instrumentation, 6(1), 2019: 1-16. https://doi.org/10.1140/epjti/s40485-019-0050-z
[12] N.-T. Nguyen, D.D. Trung, A study on the surface grinding process of the SUJ2 steel using CBN slotted grinding wheel. AIMS Materials Science, 7(6), 2020: 871-886. https://doi.org/10.3934/matersci.2020.6.871
[13] J. Martínez-Gómez, J.F. Nicolalde, Brake Disc Material Selection Based on MCDM and Simulation. Processes, 13(5), 2025: 1287. https://doi.org/10.3390/pr13051287
[14] A. Ulutaş, F. Balo, L. Sua, E. Demir, A. Topal, V. Jakovljevic, A new integrated grey MCDM model: Case of warehouse location selection. FACTA UNIVERSITATIS: Mechanical Engineering, 19(3), 2021: 515-535.
https://doi.org/10.22190/FUME210424060U
[15] D. Arsic, D. Ivkovic, R. Sudžum, D. Marinkovic, N. Komatina, Selection of Base Materials for Repair Welding Using BWM-TOPSIS and BWM-RADAR Approaches. Materials, 18(24), 2025: 5696.
https://doi.org/10.3390/ma18245696
[16] H. Taherdoost, M. Madanchian, Multi-Criteria Decision Making (MCDM) Methods and Concepts. Encyclopedia, 3(1), 2023: 77-87. https://doi.org/10.3390/encyclopedia3010006
[17] M.A.R. Ibrahim, N.I. Jaini, K.M.N. Ku Khalif, A Review of Game Theory and Multi-Criteria Decision-Making Methods with Application to the Oil Production and Price. Malaysian Journal of Applied Sciences, 7(1), 2022: 10-26. https://doi.org/10.37231/myjas.2022.7.1.298
[18] F. Aydin, B. Gümüs, Comparative analysis of multi-criteria decision making methods for the assessment of optimal SVC location. Bulletin of the Polish Academy of Sciences Technical Sciences, 70(2), 2022: e140555. https://doi.org/10.24425/bpasts.2022.140555
[19] M. Keshavarz-Ghorabaee, M. Amiri, E.K. Zavadskas, J. Antucheviciene, Simulation-Aided Analysis of a Deviation-Based Pairwise Assessment Ratio Technique (DEPART) for MCDM. International Journal of Computers Communications & Control, 20(3), 2025: 7038. https://doi.org/10.15837/ijccc.2025.3.7038
[20] K.H. Nguyen, D.V. Pham, Q.V. Tran, A multi-criteria decision-making in relieving grinding process of surface of gear milling tooth based on the archimedean spiral using TAGUCHI-AHP-TOPSIS method. EUREKA: Physics and Engineering, (4), 2023: 87-103. https://doi.org/10.21303/2461-4262.2023.002795
[21] N.V. Thanh, Sustainable Energy Source Selection for Industrial Complex in Vietnam: A Fuzzy MCDM Approach. IEEE Access, 10, 2022: 50692-50701. https://doi.org/10.1109/ACCESS.2022.3173609
[22] V. Dohale, M. Akarte, S. Gupta, V. Verma, Additive Manufacturing Process Selection Using MCDM. Lecture Notes in Mechanical Engineering, 2021: 601-609. https://doi.org/10.1007/978-981-15-3639-7_72
[23] M.d. Santos, I.P.d.A. Costa, C.F.S. Gomes, Multicriteria decision-making in the selection of warships: a new approach to the AHP method. International Journal of the Analytic Hierarchy Process, 13(1), 2021: 147-169. https://doi.org/10.13033/ijahp.v13i1.833
[24] S.H. Mian, E.A. Nasr, K. Moiduddin, M. Saleh, M.H. Abidi, H. Alkhalefah, Assessment of consolidative multi-criteria decision making (C-MCDM) algorithms for optimal mapping of polymer materials in additive manufacturing: A case study of orthotic application. Heliyon, 10(10), 2024: e30867.
https://doi.org/10.1016/j.heliyon.2024.e30867
[25] H. Zhang, Y. Peng, G. Tian, D. Wang, P. Xie, Green material selection for sustainability: A hybrid MCDM approach. PLOS One, 12(5), 2017: e0177578. https://doi.org/10.1371/journal.pone.0177578
[26] Z. Ilic, G. Marinkovic, V. Bulatovic, A. Matic, V. M. Petrovic, Comprehensive MCDM Approach in the Process of Land Consolidation Project Choice. Land, 14(9), 2025: 1798.
https://doi.org/10.3390/land14091798
[27] A. Ozcil, E. Aytac Adali, A Novel MCDM Method: The Integrative Reference Point Approach. Informatica, 36(3), 2025: 625-655. https://doi.org/10.15388/25-INFOR594
[28] A. Ulutaş, F. Balo, K. Mirković, Ž. Stević, M.M.H. Mostafa, MCDM model for critical selection of building and insulation materials for optimising energy usage and environmental effect in production focus. Journal of Civil Engineering and Management, 29(7), 2023: 587-603. https://doi.org/10.3846/jcem.2023.19569
[29] N.-T. Tran, Application of the multi-criteria analysis method MAIRCA, SPOTIS, COMET for the optimization of sustainable electricity technology development. EUREKA: Physics and Engineering, (1), 2024: 180-188. https://doi.org/10.21303/2461-4262.2024.003133
[30] S.S. Goswami, D.K. Behera, S. Mitra, C.A. Saleel, B. Saleh, A. Razak, A. Buradi, A. Ketema, Development of entropy embedded COPRAS-ARAS hybrid MCDM model for optimizing EDM parameters while machining high carbon chromium steel plate. Advances in Mechanical Engineering, 14(10), 2022: 1-17. https://doi.org/10.1177/16878132221129702
[31] A.M. Ghaleb, H. Kaid, A. Alsamhan, S.H. Mian, L. Hidri, Assessment and Comparison of Various MCDM Approaches in the Selection of Manufacturing Process. Advances in Materials Science and Engineering, 2020(1), 2020: 4039253. https://doi.org/10.1155/2020/4039253
[32] E. Pourjavad, H. Shirouyehzad, A MCDM Approach for Prioritizing Production Lines: A Case Study. International Journal of Business and Management, 6(10), 2011: 221-229.
https://doi.org/10.5539/ijbm.v6n10p221
[33] D.D. Trung, A combination method for multi-criteria decision making problem in turning process. Manufacturing Review, 8, 2021: 26. https://doi.org/10.1051/mfreview/2021024
[34] F. Hosseinzadeh Lotfi, T. Allahviranloo, W. Pedrycz, M. Shahriari, H. Sharafi, S. Razipour GhalehJough, Simple Additive Weighting (SAW) Method in Fuzzy Environment. Studies in Computational Intelligence, 1121, 2023: 117-140. https://doi.org/10.1007/978-3-031-44742-6_5
[35] I. M. Hezam, A.R. Mishra, P. Rani, A. Saha, F. Smarandach, D. Pamucar, An integrated decision support framework using single-valued neutrosophic-MASWIP-COPRAS for sustainability assessment of bioenergy production technologies. Expert Systems with Applications, 211, 2023: 118674.
https://doi.org/10.1016/j.eswa.2022.118674
[36] P. Permata, J. Wang, Setiawansyah, A.F.O. Pasaribu, A.D. Wahyudi, RAM-MEREC (Root Assessment Method – Method based on Removal Effects of Criteria): A Synergistic Approach to Weight Derivation and Alternative Ranking in the Selection of the Best Intern Employees. TIN: Terapan Informatika Nusantara, 5(11), 2025: 657-669.
[37] M. Zheng, J. Yu, Material Selection for Gear Manufacture in Terms of the Probabilistic Multi-objective Optimization. Research on Intelligent Manufacturing and Assembly, 4(1), 2025: 180-184.
https://doi.org/10.25082/RIMA.2025.01.004
[38] H. Taherdoost, Analysis of Simple Additive Weighting Method (SAW) as a MultiAttribute Decision-Making Technique: A Step-by-Step Guide. Journal of Management Science & Engineering Research, 6(1), 2023: 21-24. https://doi.org/10.30564/jmser.v6i1.5400
[39] L. Lamrini, M.C. Abounaima, M. Talibi Alaoui, New distributed-topsis approach for multi-criteria decision-making problems in a big data context. Journal of Big Data, 10, 2023: 97.
https://doi.org/10.1186/s40537-023-00788-3
[40] P.K. Chidambaram, C. Sukumaran, M. Ramachandran, V. Saravanan, K. Ramu, Optimal Supplier Selection Using MOORA MCDM Method. Lecture Notes in Networks and Systems, 1169, 2024: 637-644.
https://doi.org/10.1007/978-3-031-73324-6_61
[41] S.B. Patil, T.A. Patole, R.S. Jadhav, S.S. Suryawanshi, S.J. Raykar, Complex Proportional Assessment (COPRAS) based Multiple-Criteria Decision Making (MCDM) paradigm for hard turning process parameters. Materials Today: Proceedings, 59(1), 2022: 835-840. https://doi.org/10.1016/j.matpr.2022.01.142
[42] F. Ciardiello, A. Genovese, A comparison between TOPSIS and SAW methods. Annals of Operations Research, 325, 2023: 967-994. https://doi.org/10.1007/s10479-023-05339-w
[43] A. Shekhovtsov, How strongly do rank similarity coefficients differ used in decision making problems?. Procedia Computer Science, 192, 2021: 4570-4577. https://doi.org/10.1016/j.procs.2021.09.235
[44] A. Katrancı, N. Kundakcı, K. Arman, Fuzzy SIWEC and Fuzzy RAWEC Methods for Sustainable Waste Disposal Technology Selection. Spectrum of Operational Research, 3(1), 2026: 87-102.
https://doi.org/10.31181/sor31202633
[45] P. Aazagreyir, P. Appiahene, O. Appiah, S. Boateng, Comparative analysis of fuzzy multi-criteria decision-making methods for quality of service-based web service selection. IAES International Journal of Artificial Intelligence, 13(2), 2024: 1408-1419. https://doi.org/10.11591/ijai.v13.i2.pp1408-1419
[46] N. Komatina, D. Marinkovic, M. Babič, Fundamental Characteristics and Applicability of the RADAR Method: Proof of Ranking Consistency. Spectrum of Operational Research, 3(1), 2026: 63-80.
https://doi.org/10.31181/sor31202635
[47] S. Lakmayer, M. Danielson, Efficient Weight Ranking in Multi-Criteria Decision Support Systems. Electronics, 14(7), 2025: 1237. https://doi.org/10.3390/electronics14071237
[48] H.K. Alfares, S.O. Duuaa, Simulation-Based Evaluation of Criteria Rank-Weighting Methods in Multi-Criteria Decision-Making. International Journal of Information Technology & Decision Making, 15(01), 2016: 43-61. https://doi.org/10.1142/S0219622015500315
[49] A.R. Paramanik, S. Sarkar, B. Sarkar, OSWMI: An objective-subjective weighted method for minimizing inconsistency in multi-criteria decision making. Computers & Industrial Engineering, 169, 2022: 108138. https://doi.org/10.1016/j.cie.2022.108138
[50] Y.B. Gopisetty, H.R. Sama, Skewness impact through distributional evaluation (SITDE) method: a new method in multi-criteria decision making. Journal of the Operational Research Society, 76(6), 2025: 1204-1224. https://doi.org/10.1080/01605682.2024.2416910
[51] T. Basuri, K.H. Gazi, S.G. Das, S.P. Mondal, Ranking Higher Education Institutions Using Entropy–VIKOR with Generalized Pentagonal Intuitionistic Fuzzy Numbers. Journal of Contemporary Decision Science, 2(1), 2026: 64-83.
[52] M. Keshavarz-Ghorabaee, M. Amiri, E.K. Zavadskas, Z. Turskis, J. Antucheviciene, Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC). Symmetry, 13(4), 2021: 525. https://doi.org/10.3390/sym13040525
[53] M. Riaz, F. Qamar, S. Tariq, K. Alsager, AI-Driven LOPCOWAROMAN Framework and Topological Data Analysis Using Circular Intuitionistic Fuzzy Information: Healthcare Supply Chain Innovation. Mathematics, 12(22), 2024: 3593. https://doi.org/10.3390/math12223593
[54] Z. Gligoric, M. Gligoric, I. Miljanovic, S. Lutovac, A. Milutinovic, Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method) – Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm. Computer Modeling in Engineering & Sciences, 136(1), 2023: 955-979. https://doi.org/10.32604/cmes.2023.025021
[55] H.-J. Shyur, H.-S. Shih, Resolving Rank Reversal in TOPSIS: A Comprehensive Analysis of Distance Metrics and Normalization Methods. Informatica, 35(4), 2024: 837-858. https://doi.org/10.15388/24-INFOR576
[56] M. Socorro García-Cascales, M. Teresa Lamata, On rank reversal and TOPSIS method. Mathematical and Computer Modelling, 56(5–6), 2012: 123-132. https://doi.org/10.1016/j.mcm.2011.12.022