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Proceedings of the 2024 Ninth International Conference on Research in Intelligent Computing in Engineering

Annals of Computer Science and Information Systems, Volume 42

Comparison of SAW, RAM, and TOPSIS Methods in Multi-Criteria Decision Making: Application in Selecting Waterproofing Materials Imported From Malaysia

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DOI: http://dx.doi.org/10.15439/2024R66

Citation: Proceedings of the 2024 Ninth International Conference on Research in Intelligent Computing in Engineering, Vijender Kumar Solanki, Tran Duc Tan, Pradeep Kumar, Manuel Cardona (eds). ACSIS, Vol. 42, pages 39–47 ()

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Abstract. SAW is the oldest method among the multi-criteria decision-making (MCDM) approaches. On the other hand, RAM is known to be the newest method. TOPSIS is a highly renowned method and is the most widely used among MCDM methods. A question arises as to which method is deemed superior to the other two. The answer to this question is first found in this study. The selection of waterproofing materials is the problem used to compare the three aforementioned methods. The results indicated that RAM and TOPSIS are equally effective and superior to the SAW method.

References

  1.      https://vngeo.com/thong-so-ky-thuat-mang-chong-tham-hdpe-solmax/
  2.      https://vaidiakythuat.com/thong-so-ky-thuat-va-gia-ban-mang-chong-tham-hdpe-day-0-5mm.html
  3.      S. Kusumadewi, S. Hartati, A. Harjoko, and R. Wardoyo, Fuzzy Multi-Attribute Decision Making (FUZZY MADM), Yogyakarta: Penerbit Graha Ilmu, 2006.
  4.      Alireza Sotoudeh-Anvari, Root Assessment Method (RAM): A novel multi-criteria decision making method and its applications in sustainability challenges, Journal of Cleaner Production 423 (2023) 138695, https://doi.org/10.1016/j.jclepro.2023.138695
  5.      C. –L. Hwang, Y. –J. Lai, Ting_Yun Liu, A new approach for multiple objective decision making, Computers & Operations Research, Vol. 20, No. 8, pp. 889–899, 1993.
  6.      R. M. Dawes, B. Coorigan, Linear Models in Decision
Malking, Psychological Bulletin, Vol. 81, pp. 95–106, 1974.
  7.       Yuxin Z., Dazuo T., Feng Y., Effectiveness of Entropy Weight Method in Decision-Making, Mathematical Problems in Engineering, Vol. 2020, pp. 1–5, 2020.
  8.      Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E.K., Turskis, Z., Antucheviciene, J, Determination of objective weights using a new method based on the removal effects of criteria (MEREC), Symmetry, Vol. 13, No. 4, pp. 1-20, 2021.
  9.      Hamed Taherdoost, Analysis of Simple Additive Weighting Method (SAW) as a Multi
Attribute Decision-Making Technique: A Step-by-Step Guide, Journal of Management Science & Engineering Research, Vol. 6. No. 1, 2023, 21-24, https://doi.org/10.30564/jmser.v6i1.5400
  10.    Tran Van Dua, Combination of design of experiments and simple additive weighting methods: a new method for rapid multi-criteria decision making. EUREKA: Physics and Engineering, Vol. 2023, No. 1, 120–133, https://doi.org/10.21303/2461-4262.2023.002733
  11.    Kamala Aliyeva, Aida Aliyeva, Rashad Aliyev, Mustafa Ozdeser, Application of Fuzzy Simple Additive Weighting Method in Group Decision-Making for Capital Investment, Axioms, Vol. 12, No. 797, 2023, 1-13, https://doi.org/10.3390/axioms12080797
  12.    Ahmed E. Youssef, Kashif Saleem, A Hybrid MCDM Approach for Evaluating Web-Based E-Learning Platforms, IEEE Access, Vol. 11, 2023, 72436-72447, https://doi.org/10.1109/ACCESS.2023.3294798
  13.    Neven Saleh, Mohamed N. Gaber, Mohamed A. Eldosoky, Ahmed M. Soliman, Vendor evaluation platform for acquisition of medical equipment based on multi-criteria
decision-making approach, Scientific reports, Vol. 13, No. 12746, 2023, https://doi.org/10.1038/s41598-023-38902-3
  14.    Jiahui Su and Yidi Sun, An Improved TOPSIS Model Based on Cumulative Prospect Theory: Application to ESG Performance Evaluation of State-Owned Mining Enterprises, Sustainability, Vol. 15, No. 10046, 2023,  1-20, https://doi.org/10.3390/su151310046
  15.    Kien Huy Nguyen, Dong Van Pham, Quoc Ve 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, Vol. 2023, No. 4, 2023, 87–103, https://doi.org/10.21303/2461-4262.2023.002795
  16.    Loubna Lamrini, Mohammed Chaouki Abounaima, Mohammed Talibi Alaoui, New distributed-topsis approach for multi-criteria decision-making problems in a big data context, Journal of Big Data, Vol. 10, No. 97, 2023, 1-21, https://doi.org/10.1186/s40537-023-00788-3
  17.    Sushil Kumar Sahoo, Shankha Shubhra Goswami, A Comprehensive Review of Multiple Criteria Decision-Making (MCDM) Methods: Advancements, Applications, and Future Directions, Decision Making Advances, Vol.1, No. 1, 2023, 25-48, https://doi.org/10.31181/dma1120237
  18.    Mahmut Baydaş, Tevfik Eren, Željko Stević, Vitomir Starčević, Raif Parlakkay, Proposal for an objective binary benchmarking framework that validates each other for comparing MCDM methods through data analytics, PeerJ Computer Science, Vol. 9, No. e1350, 2023,  1-24, https://doi.org/10.7717/peerj-cs.1350
  19.    Dusko Tesic, Darko Bozanic, Dejan Stojkovic, Adis Puska, Ilija Stojanovic, DIBR–DOMBI–FUZZY MAIRCA Model for Strategy Selection in the System of Defense, Hindawi Discrete Dynamics in Nature and Society, Vol. 2023, No. 4961972, 2023, 1-14, https://doi.org/10.1155/2023/4961972
  20.    Agnieszka Tubis, Sylwia Werbinska-Wojciechowska, Fuzzy TOPSIS in selecting logistic handling operator: case study from POLAND, Transport, Vol. 38, No. 1, 2023, 12-30, https://doi.org/10.3846/transport.2023.17074
  21.    Ibrahim badi, Ali Abdulshahed, Emhemed Alghazel, Using Grey-TOPSIS approach for solar farm location selection in Libya, Reports in Mechanical Engineering, Vol. 4, No. 1, 2023, 80-89, https://doi.org/10.31181/rme040129062023b
  22.    Trung, D.D., Thinh, H.X., A multi-criteria decision-making in turning process using theMAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study, Advances in Production Engineering & Management, Vol. 16, No. 4, 2021, 443-456, https://doi.org/10.14743/apem2021.4.412
  23.    Duc Trung Do, Application of FUCA method for multi-criteria
decision making in mechanical machining processes, Operational Research in Engineering Sciences: Theory and Applications, Vol. 5, Issue 3, 2022, pp. 131-152, https://doi.org/10.31181/oresta051022061d
  24.    Mahmut Baydas, Comparison of the Performances of MCDM Methods under Uncertainty: An Analysis on Bist SME Industry Index, OPUS Journal of Society Research, Vol. 19, No. 46, 2021, 308-326, https://doi.org/10.26466//opusjsr.1064280
  25.    Mahmut Baydas, Orhan Emre Elma, An objective criteria proposal for the comparison of mcdm and weighting methods in financial performance measurement: an
application in BORSA ISTANBUL, Decision Making: Applications in Management and Engineering, Vol. 4, Issue 1, 2021, pp. 257-279, https://doi.org/10.31181/dmame210402257b