Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science

DOE-MARCOS: A NEW APPROACH TO MULTI-CRITERIA DECISION MAKing


DOI: 10.5937/jaes0-40221 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 21 article 1070 pages: 263-274

Do Duc Trung*
Faculty of Mechanical Engineering, Hanoi University of Industry

Nguyen Hong Son
Center for Mechanical Engineering, Hanoi University of Industry

Tran Trung Hieu
Center for Mechanical Engineering, Hanoi University of Industry

Vo Thi Nhu Uyen
Department of Academic Affairs, Hanoi University of Industry

Choosing the best among the available alternatives seems to be expected in all fields. As each alternative is considered by multiple criteria, the selection of the best alternative must take into account all of those criteria. MCDMs are methods that have been widely used to solve problems of this type. However, if only a certain MCDM is applied, the ranking of alternatives must be done from the beginning as adding/removing one or more alternatives from the option list. This paper presents a probably new approach to deal with this situation. DOE method was used in combination with the MARCOS method to build a relationship between the scores of the options and the criteria. This mix is called DOE-MARCOS. Based on this, the calculation of the scores of the alternatives may be faster and less complicated than only using the MCDM. A simple example was made to evaluate the effectiveness of the proposed method when an alternative was added to the list. Two other examples were also conducted to assess the performance of the proposed method (DOE-MARCOS) in ranking cutting tools. The results of ranking options using the DOE-MARCOS are compared with other methods. Sensitivity analysis in each example under different scenarios was also carried out. Its results show that the proposed method is highly effective for multi-criteria decision making.

View article

1.      Trung, D. D. (2022). Expanding data normalization method to CODAS method for multi-criteria decision making, Applied Engineering Letters, vol. 7, no. 2, 54-66, DOI: 10.18485/aeletters.2022.7.2.2

2.      Malesevic, M., Stancic, M.  (2021). Influence of packaging design parameters on customers’ decision-making process, Journal of Graphic Engineering and Design, vol. 12, no. 4,  33-38, DOI:  10.24867/JGED-2021-4-033

3.      Zopounidis, C., Doumpos, M. (2017). Multiple Criteria Decision Making - Applications in Management and Engineering. Springer, DOI: 10.1007/978-3-319-39292-9

4.      Wen, Z., Liao, H., Zavadskas, E. K. (2020). MACONT: Mixed Aggregation by Comprehensive
Normalization Technique for Multi-Criteria Analysis. Informatica, vol. 31, no. 4, 857–880, DOI: 10.15388/20-INFOR417

5.      Vafaei, N., Ribeiro, R. A., Camarinha-Matos, L. M. (2018). Data normalisation techniques in decision making: case study with TOPSIS method. International Journal of Information and Decision Sciences, vol. 10, no. 1 19-38, DOI: 10.1504/IJIDS.2018.090667

6.      Ersoy, N. (2021). Selecting the Best Normalization Technique for ROV Method: Towards a Real Life Application. Gazi University Journal of Science, vol. 34, no. 2, 592-609, DOI: 10.35378/gujs.767525

7.      Aytekin, A. (2021). Comparative Analysis of the Normalization Techniques in the Context of MCDM Problems. Decision Making: Applications in Management and Engineering, vol. 4, no. 2, 1-27, DOI: 10.31181/dmame210402001a

8.      Trung, D. D. (2022). Comparison R and CURLI methods for multi-criteria decision making, Advanced Engineering Letters, vol. 1, no. 2, 46-56, DOI: 10.46793/adeletters.2022.1.2.3

9.      Trung, D. D. (2022). Multi-criteria decision making under the MARCOS method and the weighting methods: applied to milling, grinding and turning processes. Manufacturing Review, vol. 9, no. 3, 1-13, DOI: 10.1051/mfreview/2022003

10.   Trung, D. D. (2021). Application of TOPSIS an PIV Methods for Multi - Criteria Decision Making in Hard Turning Process. Journal of Machine Engineering. vol. 21, no. 4, 57-71, DOI: 10.36897/jme/142599

11.   Stevic, Z., Pamucar, D., Puska, A., Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS). Computers & Industrial Engineering, vol. 140, 1–33, DOI: 10.1016/j.cie.2019.106231

12.   Trung, D. D. (2022). Development of data normalization methods for multi-criteria decision making: applying for MARCOS method, Manufacturing Review, vol. 9, no. 22, 1-15, DOI: 10.1051/mfreview/2022019

13.   Stevic, Z., Brkovic, N. (2020). A Novel Integrated FUCOM-MARCOS Model for Evaluation of Human Resources in a Transport Company. Logistic, vol. 4, no. 1, 1-14, DOI: 10.3390/logistics4010004

14.   Ulutas, A., Karabasevic, D., Popovic, G., Stanujkic, D., Nguyen, P. T., Karakoy, C. (2020). Development of a Novel Integrated CCSD-ITARA-MARCOS Decision-Making Approach for Stackers Selection in a Logistics System. Mathematic, vol. 8, no. 10, 1-15, DOI: 10.3390/math8101672

15.   Nandi, S., Ghosh, R. K., Ghosh, S., Jana, S., Ghosh, A., Ghorui, N., Azevedo, P. S. (2022). Ranking of Financial Apps using Fuzzy AHP and Fuzzy MARCOS: An Application of Multi-Criteria Decision-Making (MCDM) Techniques.  Available at SSRN, 1-25,  DOI: 10.2139/ssrn.4188475

16.   Ecer, F., Pamuca, D. (2021). MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services. Applied Soft Computing Journal, vol. 104, 1-18, DOI: 10.1016/j.asoc.2021.107199

17.   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 Science, vol. 12, no. 8, 2022, 1-11, DOI: 10.3390/app12083720

18.   Kovac, M., Tadic, S., Krstic, M., Bouraima, M. B. (2021). Novel Spherical Fuzzy MARCOS Method for Assessment of Drone-Based City Logistics Concepts. Hindawi Complexity, Vol. 2021, 1-17, DOI: 10.1155/2021/2374955

19.   Puska, A., Stevic, Z., Stojanovic, I. (2021). Selection of Sustainable Suppliers Using the Fuzzy MARCOS Method. Current Chinese Science, vol. 1, 218-229.

20.   Maihemuti, S., Wang, W., Wu, J., Wang, H. (2022). New energy power system operation security evaluation based on the SWOT analysis. Scicentific reports, vol. 12, 1-14, DOI: 10.1038/s41598-022-16444-4

21.   Saha, A., Mishra, A. R., Rani, P. (2021). FUCOM-MARCOS based Group Decision-making using Dombi Power Aggregation of Dual Probabilistic Linguistic Information. Research square, Vol. 2021, 1-30, DOI: 10.21203/rs.3.rs-371236/v1

22.   Badi, I., Muhammad, L. J., Abubakar, M., Bakır, M. (2022). Measuring sustainability performance indicators using FUCOM – MARCOS methods, Operational Research in Engineering Sciences: Theory and Applications, vol. 5, no. 2, 99-116, DOI:  10.31181/oresta040722060b

23.   Bouraima, M. B., Stevic, Z., Tanackov, I., Qiu, Y. (2021). Assessing the performance of Sub-Saharan African (SSA) railways based on an integrated Entropy – MARCOS approach, Operational Research in Engineering Sciences: Theory and Applications, vol. 4, no. 2, 13-35, DOI: 0.31181/oresta20402013

24.   Trung, D. D. (2020). Influence of Cutting Parameters on Surface Roughness during Milling AISI 1045 Steel. Tribology in Industry, vol. 42, no. 4, 658-665, DOI: 10.24874/ti.969.09.20.11

25.   Dean, A., Voss, D., Draguljić, D. (2007). Design and Analysis of Experiments - Second Edition. Springer.

26.   Trung, D. D. (2021). Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel. Tribology in Industry, vol. 43, no. 1, 167-176, DOI: 10.24874/ti.1009.11.20.01

27.   Calıskan, H. (2013). Selection of boron based tribological hard coatings using multi-criteria decision making methods. Materials and Design, vol.  50, 742–749, DOI: 10.1016/j.matdes.2013.03.059

28.   Pamucar, D., Bozanic, D., Randelovic, A. (2017). Multi-criteria decision making: An example of sensitivity analysis. Serbian Journal of Management, vol. 12, no. 1, DOI: 10.5937/sjm12-9464

29.   Trung, D. D., Thinh, H. X. (2021). A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study. Advances in Production Engineering & Management, vol. 16, no. 4, 443-456, DOI:  10.14743/apem2021.4.412

30.   Trung, D. D., Nhu-Tung, N. (2022). Applying Cocoso, Mabac, Mairca, Eamr, Topsis and Weight Determination Methods for Multi-Criteria Decision Making in Hole Turning Process. Strojnícky časopis - Journal of Mechanical Engineering, vol. 72, no. 2, 15-40, 2022, DOI: 10.2478/scjme-2022-0014

31.   Einhorn, H. J., Mccoach, W. (1997). A Symble Multiattribute Utility Procedure for Evaluation. Behavioral Scicence, vol. 22, no. 4, 270–282, DOI: 10.1002/bs.3830220405

32.   Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E.K., Turskis, Z., Antucheviciene, J. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Symmetry. vol. 13, no. 4, Article No. 525, DOI: 10.3390/sym13040525

33.   Trung, D. D., Nguyen, N. T., Duc, D. V. (2021). Study on multi-objective optimization of the turning process of EN 10503 steel by combination of Taguchi method and Moora technique. EUREKA: Physics and Engineering, vol. 2021, no. 2, 52-65, DOI: 10.21303/2461-4262.2020.001414

34.   Chatterjee, P., Chakraborty, S. (2016). A comparative analysis of VIKOR method and its variants. Decision Science Letters, vol. 5, 469–486, DOI: 10.5267/j.dsl.2016.5.004