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Comparative Results of Ranking of Alternatives Using Different Normalization Methods: Computational Experiment

In: Normalization of Multidimensional Data for Multi-Criteria Decision Making Problems

Author

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  • Irik Z. Mukhametzyanov

    (Ufa State Petroleum Technological University)

Abstract

This chapter presents a comparative analysis of the ranking of alternatives when applying various normalization methods based on a numerical experiment. Calculations and analysis were performed for two problems of multi-criteria choice. The first problem has a weak sensitivity to the normalization method, and the second one has a strong sensitivity. Both problems (decision matrices) are described in Chap. 6 . 238 different rank models are built, combining 13 aggregation methods and 21 different normalization methods, all other things being equal. To compare the results, the ranking was also performed within seven outranking models that do not use data normalization. The ranking results for 238 different models are aggregated under the Borda voting concept, in which different models are defined as “electors.” The use of a many number of models or a computational experiment makes it possible to establish the sensitivity of the multi-criteria choice problem to the decision matrix normalization procedure.

Suggested Citation

  • Irik Z. Mukhametzyanov, 2023. "Comparative Results of Ranking of Alternatives Using Different Normalization Methods: Computational Experiment," International Series in Operations Research & Management Science, in: Normalization of Multidimensional Data for Multi-Criteria Decision Making Problems, chapter 0, pages 221-246, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-33837-3_11
    DOI: 10.1007/978-3-031-33837-3_11
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