WEBIRA - Comparative Analysis of Weight Balancing Method

Aleksandras Krylovas, Natalja Kosareva, Edmundas Kazimieras Zavadskas

Abstract


The attributes weight establishing problem is one of the most important MCDM tasks. This study summarizes weight determining approach which is called WEBIRA (WEight Balancing Indicator Ranks Accordance). This method requires to solve complicated optimization problem and its application is possible by carrying out non trivial calculations. The efficiency of WEBIRA and other MCDM methods – SAW (Simple Additive Weighting) and EMDCW (Entropy Method for Determining the Criterion Weight) compared for 4 different data normalization methods. The results of the study revealed that more sophisticated WEBIRA method is significantly efficient for all considered numbers of alternatives. Efficiency of all methods decreases with increasing number of alternatives, but WEBIRA is still applicable, while application of other methods is impossible as the number of alternatives is greater than 11. WEBIRA is the least affected by the data normalization, while EMDCW is the most affected method.

Keywords


WEBIRA, SAW, EMDCW, multi-attribute decision making (MADM), entropy, KEMIRA

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References


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DOI: https://doi.org/10.15837/ijccc.2017.2.2844



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