Combination of design of experiments and simple additive weighting methods: a new method for rapid multi-criteria decision making

Keywords: MCDM, DOE method, SAW method, DOESAW method, Rapid decision making

Abstract

Multi-criteria decision making to choose the best option is a complicated task but a required activity in all fields. The problem will be more complicated if, after making a decision, one/several options are added to the list of options to be ranked. In this case, if only a certain multi-criteria decision making method is used, the decision-making shall be required to be started over again. This study recommends a simple solution to overcome this situation. The recommended solution is a combination between the Design Of Experiments method and a certain multi-criteria decision making method. Simple Additive Weighting method was selected in this study as one of the multi-criteria decision making methods for testing. Use the Design Of Experiments method to design an experiment matrix with the main input parameters being the criteria of options. The Simple Additive Weighting method is applied to calculate the output value of each experiment, called the score of the experiment. Develop a mathematical relation between the scores of the experiments and the criteria. This relation is used to recalculate the scores for options to be ranked. Three different cases were performed to evaluate the effectiveness of the new method. The results of ranking alternatives by new method have been compared with when using other methods. Sensitivity analysis was also performed in each case. The generation of different scenarios is done using different methods to determine the weights for the criteria. The best alternative determined when using the new method is always similar to when using other methods. In addition, when using the new method, the best alternative is determined regardless of the method of determining the weights for the criteria. The obtained results have proved the accuracy of the methodology and the advantages of the recommended method. Future work is also mentioned in the last part of this article

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Author Biography

Tran Van Dua, Hanoi University of Industry

Faculty of Mechanical Engineering

References

Zopounidis, C., Doumpos, M. (Eds.) (2017). Multiple Criteria Decision Making. Applications in Management and Engineering. Springer, 211. doi: https://doi.org/10.1007/978-3-319-39292-9

Prasetiyo, B., Baroroh, N. (2016). Fuzzy Simple Additive Weighting Method in the Decision Making of Human Resource Recruitment. Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, 7 (3), 174. doi: https://doi.org/10.24843/lkjiti.2016.v07.i03.p05

Vafaei, N., Ribeiro, R. A., Camarinha-Matos, L. M. (2022). Assessing Normalization Techniques for Simple Additive Weighting Method. Procedia Computer Science, 199, 1229–1236. doi: https://doi.org/10.1016/j.procs.2022.01.156

Goodridge, W. S. (2016). Sensitivity Analysis Using Simple Additive Weighting Method. International Journal of Intelligent Systems and Applications, 8 (5), 27–33. doi: https://doi.org/10.5815/ijisa.2016.05.04

Pangaribuan, I., Beniyanto, A. (2020). Multi-criteria decision-making method for procurement of goods and services auction system. Journal of Engineering Science and Technology, Special Issue on INCITEST2020, 26–32. Available at: https://jestec.taylors.edu.my/Special%20Issue%20INCITEST2020/INCITEST2020_04.pdf

Mitra, S., Goswami, S. S. (2019). Application of Simple Average Weighting Optimization Method in the Selection of Best Desktop Computer Model. Advanced Journal of Graduate Research, 6 (1), 60–68. doi: https://doi.org/10.21467/ajgr.6.1.60-68

Salehi, A., Izadikhah, M. (2014). A novel method to extend SAW for decision-making problems with interval data. Decision Science Letters, 3 (2), 225–236. doi: https://doi.org/10.5267/j.dsl.2013.11.001

Afshari, A., Mojahed, M., Yusuff, R. M. (2010). Simple Additive Weighting approach to Personnel Selection problem. International Journal of Innovation, Management and Technology, 1 (5), 511–515. Available at: http://ijimt.org/papers/89-M474.pdf

Abdullah, L., Zamri, N., Goh, C. M. (2019). Application of Interval Type 2 Fuzzy SAW in Flood Control Project. International Journal of Advances in Soft Computing and its Applications, 11 (3), 124–137. Available at: http://www.i-csrs.org/Volumes/ijasca/8_p124-137_Application%20of%20Interval%20Type%202%20Fuzzy%20SAW%20in%20Flood%20Control%20Project.pdf

Vujicic, M., Papic, M., Blagojevic, M. (2017). Comparative analysis of objective techniques for criteria weighing in two MCDM methods on example of an air conditioner selection. Tehnika, 72 (3), 422–429. doi: https://doi.org/10.5937/tehnika1703422v

Ajay, D., Manivel, M., Aldring, J. (2019). Neutrosophic Fuzzy SAW Method and It’s Application. The International journal of analytical and experimental modal analysis, 11 (8), 881–887. Available at: https://www.researchgate.net/publication/343761247_Neutrosophic_Fuzzy_SAW_Method_and_It's_Application

Zein Eldin, R. A., Abdullah, B. M. (2017). Comparing Two Multi-Criteria Approaches to Investigate Their Ability in Measuring Efficiency. International Journal for Modern Trends in Science and Technology, 03 (02), 52–56. Available at: http://ijmtst.com/vol3issue2/256IJMTST030237.pdf

Gokgoz, F., Yalcın, E. (2019). An Integrated Approach to the World Cup Teams using Entropy based ARAS and SAW Methods. ILLHSS-19, ICIIT-19, IABMS-19. Istanbul. doi: https://doi.org/10.17758/uruae8.uh12194007

Panjaitan, M. I. (2019). Simple Additive Weighting (SAW) method in Determining Beneficiaries of Foundation Benefits. Jurnal Teknologi Komputer, 13 (1), 19–25. Available at: https://media.neliti.com/media/publications/326766-simple-additive-weighting-saw-method-in-f8f093e8.pdf

Larasati, P. D., Irawan, A. (2020). Application for Lecturer Recruitment Using Simple Additive Weighting (SAW) Method Case Study: Tanri Abeng University Jakarta. Applied Information System and Management (AISM), 3 (1), 15–20. doi: https://doi.org/10.15408/aism.v3i1.9184

Loa, A., Daniawan, B., Tugiman, T., Basri, A. (2020). Comparing SAW and CPI Method in Decisions Systems Support to Evaluate Teachers Performance. bit-Tech, 2 (3), 121–130. Available at: https://jurnal.kdi.or.id/index.php/bt/article/view/141

Cahyapratama, A., Sarno, R. (2018). Application of Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods in singer selection process. 2018 International Conference on Information and Communications Technology (ICOIACT). doi: https://doi.org/10.1109/icoiact.2018.8350707

Dobrovolskienė, N., Pozniak, A. (2021). Simple Additive Weighting versus Technique for Order Preference by Similarity to an Ideal Solution: which method is better suited for assessing the sustainability of a real estate project. Entrepreneurship and Sustainability Issues, 8 (4), 180–196. doi: https://doi.org/10.9770/jesi.2021.8.4(10)

Biswas, T. K., Chaki, S. (2022). Applications of Modified Simple Additive Weighting Method in Manufacturing Environment. International Journal of Engineering, 35 (04), 830–836. doi: https://doi.org/10.5829/ije.2022.35.04a.23

Kusumadewi, S., Hartati, S., Harjoko, A., Wardoyo, R. (2006). Fuzzy Multi-Attribute Decision Making (FUZZY MADM). Yogyakarta: Penerbit Graha Ilmu.

Singh, R., Dureja, J. S., Dogra, M., Randhawa, J. S. (2019). Optimization of machining parameters under MQL turning of Ti-6Al-4V alloy with textured tool using multi-attribute decision-making methods. World Journal of Engineering, 16 (5), 648–659. doi: https://doi.org/10.1108/wje-06-2019-0170

Dean, A., Voss, D., Draguljić, D. (2007). Design and Analysis of Experiments. Springer, 840. doi: https://doi.org/10.1007/978-3-319-52250-0

Duc Trung, D. (2021). A combination method for multi-criteria decision making problem in turning process. Manufacturing Review, 8, 26. doi: https://doi.org/10.1051/mfreview/2021024

Trung, D. D. (2020). Influence of Cutting Parameters on Surface Roughness during Milling AISI 1045 Steel. Tribology in Industry, 42 (4), 658–665. doi: https://doi.org/10.24874/ti.969.09.20.11

Trung, D. D. (2021). Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel. Tribology in Industry, 43 (1), 167–176. doi: https://doi.org/10.24874/ti.1009.11.20.01

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, 16 (4), 443–456. doi: https://doi.org/10.14743/apem2021.4.412

Trung, D. D. (2021). Application of EDAS, MARCOS, TOPSIS, MOORA and PIV Methods for Multi-Criteria Decision Making in Milling Process. Strojnícky Časopis - Journal of Mechanical Engineering, 71 (2), 69–84. doi: https://doi.org/10.2478/scjme-2021-0019

Ghorabaee, M. K., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation and Economic Cybernetics Studies and Research, 50 (3), 25–44. Available at: https://ideas.repec.org/a/cys/ecocyb/v50y2016i3p25-44.html

Combination of design of experiments and simple additive weighting methods: a new method for rapid multi-criteria decision making

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Published
2023-01-19
How to Cite
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
Section
Engineering