Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.298612

Keywords:

multi-criteria decision making, RAMDOE method, RAM method, DOE method

Abstract

This paper delves into the development and validation of the RAMDOE method, a pioneering approach in multi-criteria decision making (MCDM) that seamlessly integrates the root assessment method (RAM) and design of experiments (DOE) techniques, addressing the inflexibility of traditional MCDM methods in accommodating adjustments in criteria ranges and the addition of new alternatives without necessitating a complete overhaul of the decision framework. Through empirical analysis, the study demonstrates the RAMDOE method's remarkable efficacy in precisely ranking alternatives, as illustrated through a practical case study focused on the selection of a supplier from a pool of seven candidates. One of the most notable aspects of the RAMDOE method lies in its capacity to formulate a regression equation that accurately captures the intricate relationship between alternative scores and criteria values, enabling decision-makers to seamlessly integrate new alternatives into the decision-making process without the cumbersome task of recalibration, thereby distinguishing it from conventional MCDM techniques such as TOPSIS (technique for order of preference by similarity to ideal solution), COPRAS (complex proportional assessment), MOORA (multiobjective optimization on the basis of ratio analysis), EDAS (evaluation based on distance from average solution) and CODAS (combinative distance-based assessment). The practical implications of these findings are profound, offering decision-makers across various domains a more efficient and adaptable framework to navigate complex decision scenarios. Particularly in contexts like supplier selection, where criteria ranges may vary significantly, the RAMDOE method provides decision-makers with a robust toolset to make informed decisions, presenting a promising avenue for addressing the dynamic nature of decision-making environments and enhancing the overall robustness and flexibility of MCDM processes in real-world applications

Author Biographies

Do Duc Trung, Hanoi University of Industry

Associate Professor of Mechanical Engineering

School of Mechanical and Automotive Engineering

Tran Van Dua, Hanoi University of Industry

Doctor of Mechanical Engineering

School of Mechanical and Automotive Engineering

References

  1. Baydaş, M., Eren, T., Stević, Ž., Starčević, V., Parlakkaya, R. (2023). Proposal for an objective binary benchmarking framework that validates each other for comparing MCDM methods through data analytics. PeerJ Computer Science, 9, e1350. https://doi.org/10.7717/peerj-cs.1350
  2. Bošković, S., Švadlenka, L., Jovčić, S., Dobrodolac, M., Simić, V., Bacanin, N. (2023). An Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) – A Case Study of the Electric Vehicle Selection Problem. IEEE Access, 11, 39496–39507. https://doi.org/10.1109/access.2023.3265818
  3. Puška, A., Stević, Ž., Pamučar, D. (2021). Evaluation and selection of healthcare waste incinerators using extended sustainability criteria and multi-criteria analysis methods. Environment, Development and Sustainability, 24 (9), 11195–11225. https://doi.org/10.1007/s10668-021-01902-2
  4. Krstić, M., Agnusdei, G. P., Miglietta, P. P., Tadić, S., Roso, V. (2022). Applicability of Industry 4.0 Technologies in the Reverse Logistics: A Circular Economy Approach Based on COmprehensive Distance Based RAnking (COBRA) Method. Sustainability, 14 (9), 5632. https://doi.org/10.3390/su14095632
  5. Zakeri, S., Chatterjee, P., Konstantas, D., Shojaei Farr, A. (2023). Introducing alternatives ranking with elected nominee (arwen) method: a case study of supplier selection. Technological and Economic Development of Economy, 29 (3), 1080–1126. https://doi.org/10.3846/tede.2023.18789
  6. Urošević, K., Gligorić, Z., Miljanović, I., Beljić, Č., Gligorić, M. (2021). Novel Methods in Multiple Criteria Decision-Making Process (MCRAT and RAPS) – Application in the Mining Industry. Mathematics, 9 (16), 1980. https://doi.org/10.3390/math9161980
  7. Dua, T. V. (2023). Combination of design of experiments and simple additive weighting methods: a new method for rapid multi-criteria decision making. EUREKA: Physics and Engineering, 1, 120–133. https://doi.org/10.21303/2461-4262.2023.002733
  8. Duc, T., Hong, S., Trung, H., Thi, N. (2023). DOE-MARCOS: A new approach to multi-criteria decision making. Journal of Applied Engineering Science, 21 (2), 263–274. https://doi.org/10.5937/jaes0-40221
  9. Duc, T., Ngoc, T. (2023). Combination of DOE and PIV methods for multi-criteria decision making. Journal of Applied Engineering Science, 21 (2), 361–373. https://doi.org/10.5937/jaes0-41482
  10. Chattopadhyay, R., Das, P. P., Chakraborty, S. (2022). Development of a Rough-MABAC-DoE-based Metamodel for Supplier Selection in an Iron and Steel Industry. Operational Research in Engineering Sciences: Theory and Applications, 5 (1), 20–40. https://doi.org/10.31181/oresta190222046c
  11. Chatterjee, P., Banerjee, A., Mondal, S., Boral, S., Chakraborty, S. (2018). Development of a Hybrid Meta-Model for Material Selection Using Design of Experiments and EDAS Method. Engineering Transactions, 66 (2), 187–207. https://doi.org/10.24423/engtrans.812.2018
  12. Trung, D. D., Truong, N. X., Dung, H. T., Ašonja, A. (2024). Combining DOE and EDAS Methods for Multi-criteria Decision Making. 32nd International Conference on Organization and Technology of Maintenance (OTO 2023), 210–227. https://doi.org/10.1007/978-3-031-51494-4_19
  13. Sotoudeh-Anvari, A. (2023). Root Assessment Method (RAM): A novel multi-criteria decision making method and its applications in sustainability challenges. Journal of Cleaner Production, 423, 138695. https://doi.org/10.1016/j.jclepro.2023.138695
  14. Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57 (9), 2501–2519. https://doi.org/10.1108/md-05-2017-0458
  15. Trung, D. D. (2021). Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel. Tribology in Industry, 43 (1), 167–176. https://doi.org/10.24874/ti.1009.11.20.01
  16. Do Duc, T., Nguyen Van, C., Nguyen Ba, N., Nguyen Nhu, T., Hoang Tien, D. (2020). Surface Roughness Prediction in CNC Hole Turning of 3X13 Steel using Support Vector Machine Algorithm. Tribology in Industry, 42 (4), 597–607. https://doi.org/10.24874/ti.940.08.20.11
  17. Palczewski, K., Sałabun, W. (2019). Influence of various normalization methods in PROMETHEE II: an empirical study on the selection of the airport location. Procedia Computer Science, 159, 2051–2060. https://doi.org/10.1016/j.procs.2019.09.378
  18. Pamučar, D., Behzad, M., Božanić, D., Behzad, M. (2021). Decision making to support sustainable energy policies corresponding to agriculture sector: Case study in Iran’s Caspian Sea coastline. Journal of Cleaner Production, 292, 125302. https://doi.org/10.1016/j.jclepro.2020.125302
  19. Ha, L. D. (2023). Selection of Suitable Data Normalization Method to Combine with the CRADIS Method for Making Multi-Criteria Decision. Applied Engineering Letters: Journal of Engineering and Applied Sciences, 8 (1), 24–35. https://doi.org/10.18485/aeletters.2023.8.1.4
  20. 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
Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values

Downloads

Published

2024-04-30

How to Cite

Trung, D. D., & Dua, T. V. (2024). Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values. Eastern-European Journal of Enterprise Technologies, 2(4 (128), 6–12. https://doi.org/10.15587/1729-4061.2024.298612

Issue

Section

Mathematics and Cybernetics - applied aspects