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Influence of the Different Measurement Scale and Normalization Method on Results in Topsis


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1 Business Studies and Development Office, Saipa Yadak, Iran, Islamic Republic of
     

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The present study presents a comparative analysis of different measurement scale (i.e. linear, power, and so on) and normalization method (i.e. vector, linear, and so on.) in TOPSIS, by testing them against conventional TOPSIS assumption (in the absence of any other standards, the priorities provided by the conventional TOPSIS was used as the benchmark). In this study, the following two questions are considered:1. Does a decision priorities changed when using different measurement scale and normalization method? and 2. Does the same results of the conventional TOPSIS, be obtained from the modified TOPSIS (in other words: TOPSIS with different measurement scale and normalization method)? It is shown that, the different measurement scale and normalization method can be lead to different priorities (rank and preference intensities). Also, the modified TOPSIS priorities (TOPSIS with geometric measurement scale and logarithmic normalization method), the only or best combination that is roughly equivalent priorities as compared with conventional TOPSIS. So, we suggest (after the more experimental research in future) the modified TOPSIS method as the alternative solution.

Keywords

TOPSIS, Modified TOPSIS, Measurement Scale, Normalization Method.
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  • Deng H. et al., 2000,"inter company comparison using modified topsis with objective weights", computer & operations research, 27, 963-973.

  • Hwang C. L. and K. Yoon, 1981,"multiple attribute decision making; methods and applications", Springer Verlag, 1981.

  • Irvani Z. et al. , 2009, "an algorithm for the calculation of progress or regress via topsis and malmquist productivity index", Applied Mathematical Science, vol. 3, no. 52, 2553-2562.

  • Ishizaka A. et al., 2011, "Influence of Aggregation and Measurement Scale on Ranking a compromise Alternative in AHP", journal of the operational research society, 62(4), 700-710.

  • Lin Y. H. et al., 2008, "multi attribute group decision making model under the condition of uncertain information", Automation in construction, 17 (2008) 792-797.

  • Luce R.D., 1997,"Quantification and Symmetry", British journal of Psychology, 88,395-398.

  • Olson D. L., 2004, "comparison of weights in topsis models", Mathematical and Computer Modeling, Pergamon, 1 : 1-7.

  • Pavl D.M., 2000, "Normalization of attribute values in MADM violates the conditions of consistent choice IV, DI and α ", Yugoslav journal of operations research, 1,109-122.

  • Ramanathan R., 2001, "A note to the use of the AHP for environmental impact assessment”, journal of Environmental Management, 63, 27-35.

  • Ren L. et al.,2007,"comparative analysis of a novel M-topsis method and topsis", Applied Mathematics Research Express, vol. 2007, 1-10.

  • Roghanian et al. (2010),comparison of first aggregation and last aggregation in fuzzy group TOPSIS. Applied mathematical modeling, 34 (2010), 3754-3766.

  • Stevens S. S. , 1946,"On the theory of scales of measurement", SCIENCE, 103, No.2684, 677-680.

  • Tayeb S. et al., 2007, "equipment selection by numerical resolution of the Hessian matrix and topsis algorithm", Asian Journal of Information Technology, 6(1), 81-88.

  • Yue Z., 2013, "An avoiding information approach to group decision making", Applied mathematical Modeling, Vol. 37 (2013), 112-126.

  • Zavadeskas E. K. et al.,2006,"evaluation of ranking accuracy in multi criteria decisions", Informatica, vol. 17, no. 4, 601-618.

  • Zavadskas E.K. and Z. Turskis, 2008"A new Logarithmic Normalization method in Game theory", Informatica 19, No.2, 303-314.

  • Zavadskas E.K. et al., 2010,"Attributes weights determining peculiarities in Multiple Attribute Decision Making methods", Engineering Economics, 21(1), 32-43.


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  • Influence of the Different Measurement Scale and Normalization Method on Results in Topsis

Abstract Views: 290  |  PDF Views: 4

Authors

Mohammad Azadfallah
Business Studies and Development Office, Saipa Yadak, Iran, Islamic Republic of

Abstract


The present study presents a comparative analysis of different measurement scale (i.e. linear, power, and so on) and normalization method (i.e. vector, linear, and so on.) in TOPSIS, by testing them against conventional TOPSIS assumption (in the absence of any other standards, the priorities provided by the conventional TOPSIS was used as the benchmark). In this study, the following two questions are considered:1. Does a decision priorities changed when using different measurement scale and normalization method? and 2. Does the same results of the conventional TOPSIS, be obtained from the modified TOPSIS (in other words: TOPSIS with different measurement scale and normalization method)? It is shown that, the different measurement scale and normalization method can be lead to different priorities (rank and preference intensities). Also, the modified TOPSIS priorities (TOPSIS with geometric measurement scale and logarithmic normalization method), the only or best combination that is roughly equivalent priorities as compared with conventional TOPSIS. So, we suggest (after the more experimental research in future) the modified TOPSIS method as the alternative solution.

Keywords


TOPSIS, Modified TOPSIS, Measurement Scale, Normalization Method.

References