The Robustness of TOPSIS Results Using Sensitivity Analysis Based on Weight Tuning
Multiple-criteria decision analysis (MCDA) is one of the support techniques for Health Technology Assessment (HTA). A typical method is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The output of TOPSIS presents an order of alternatives. A significant risk may be posed by an inappropriate setup of the weights of the criteria such that a very small deviation from the proper value could substantially change the final result. Sensitivity analysis is a method for testing changes of the final order by a modification of the original input data or by small deviation of the original weights of the criteria. This original approach is very slow and computationally demanding in the case of a change of the value of any attribute. The newly proposed method is significantly faster, making it possible to change of the values of the weights by only a few computations within TOPSIS. In the first stage, TOPSIS is used to compute the values of the Positive and Negative Ideal Solutions (PIS and NIS), and sensitivity analysis is only performed for the changed weights in the next stage. In the proposed method, a weight is adjusted (and the other weights recalculated) in order to find a range where the order of the alternatives remains unchanged for the modified weights. The weight adjustment can have the form of a fixed change or of an iterative process approximating the stability range for the weight. The new method is fast and simple to implement, providing a robust output of TOPSIS and pointing out a possible wrong setup of the initial weight(s).
KeywordsSensitivity analysis MCDA TOPSIS HTA
This article presents one of the results of my Master’s thesis written under the supervision of Ing. Ivana Kubátová, Ph.D. .
Conflict of Interest
The author declares that he has no conflict of interest.
- 1.EUnetHTA JA2; Joint Action on HTA 2012–2015 Methodological Standards and Procedures (MSP) for Full core HTA content development. (2015)Google Scholar
- 2.Hwang, C.-L., Yoon, K.: Multiple Attribute Decision Making. Springer Berlin Heidelberg, Berlin, Heidelberg (1981)Google Scholar
- 3.Vafaei, N., Ribeiro, R.A., Camarinha-Matos, L.M.: Normalization Techniques for Multi-Criteria Decision Making. In: Liu, S., Delibašić, B., Linden, I., and Oderanti, F.O. (eds.) THE EWG-DSS 2016 Int. Conference On Decision Support System Technology (ICDSST 2016): Decision Support Systems Addressing Sustainability & Societal Challenges. pp. 23–25, Plymouth, (2016)Google Scholar
- 4.Alinezhad, A., Amini, A.: Sensitivity Analysis of TOPSIS Technique : The Results of Change in the Weight of One Attribute on the Final Ranking of Alternatives. J. Optim. Ind. Eng. 7, 23–28 (2011)Google Scholar
- 5.Li, D.-F., Nan, J.-X.: Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments. Int. J. Fuzzy Syst. Appl. 1, 47–61 (2011). https://doi.org/10.4018/ijfsa.2011100104
- 6.Abou-el-enien, T.H.M., Abo-sinna, M.A.: Interactive TOPSIS Algorithm for Fuzzy Large Scale Two-Level Linear Multiple Objective Programming Problems. 869, 152–163 (2015)Google Scholar
- 7.Igoulalene, I., Benyoucef, L., Tiwari, M.K.: Novel fuzzy hybrid multi-criteria group decision making approaches for the strategic supplier selection problem. Expert Syst. Appl. 42, 3342–3346 (2015). https://doi.org/10.1016/j.eswa.2014.12.014
- 8.Duckstein, L., Opricovic, S.: Multiobjective optimization in river basin development. Water Resour. Res. 16, 14–20 (1980). https://doi.org/10.1029/wr016i001p00014
- 9.Opricovic, S., Tzeng, G.H.: Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 156, 445–455 (2004). https://doi.org/10.1016/s0377-2217(03)00020-1
- 10.Opricovic, S., Tzeng, G.H.: Extended VIKOR method in comparison with outranking methods. Eur. J. Oper. Res. 178, 514–529 (2007). https://doi.org/10.1016/j.ejor.2006.01.020
- 11.Afful-Dadzie, E., Nabareseh, S., Oplatková, Z.K., Klímek, P.: Model for Assessing Quality of Online Health Information: A Fuzzy VIKOR Based Method. J. Multi-Criteria Decis. Anal. 23, 49–62 (2016). https://doi.org/10.1002/mcda.1558
- 12.Millek, J.: Draft analytical tools for multi-criteria decision-making in HTA, (2017)Google Scholar