A Study on Evaluation Metrics for Multi Criteria Decision Making (MCDM) Methods - TOPSIS, COPRAS & GRA
A. Martin, T. Miranda Lakshmi, V. Prasanna Venkatesan
Abstract
A. Martin, T. Miranda Lakshmi, V. Prasanna Venkatesan
Abstract
Metrics are units of measurement. It is frequently used to mean a set of specific measurements taken on a particular process. They are very important to estimate the performance of any application. In this study, Multi Criteria Decision Making MCDM methods such as Technique for Order of Preference by Similarity to Ideal Solution TOPSIS, Complex Proportional Assessment COPRAS and Grey Relational Analysis GRA are taken into consideration. MCDM methods are applied to solve decision problems with different number of conflicting criteria. Generally these techniques are evaluated using the parameters such as time complexity, space complexity, sensitivity analysis and rank reversal. In addition to these existing evaluation parameters two new evaluation parameters such as rank occurrence and repeated ranking are designed. Hence metrics are designed for these evaluation parameters.
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Metrics are units of measurement. It is frequently used to mean a set of specific measurements taken on a particular process. They are very important to estimate the performance of any application. In this study, Multi Criteria Decision Making MCDM methods such as Technique for Order of Preference by Similarity to Ideal Solution TOPSIS, Complex Proportional Assessment COPRAS and Grey Relational Analysis GRA are taken into consideration. MCDM methods are applied to solve decision problems with different number of conflicting criteria. Generally these techniques are evaluated using the parameters such as time complexity, space complexity, sensitivity analysis and rank reversal. In addition to these existing evaluation parameters two new evaluation parameters such as rank occurrence and repeated ranking are designed. Hence metrics are designed for these evaluation parameters.
Key concepts: TOPSIS, Multiple-criteria decision analysis, Ranking (information retrieval), Ideal solution, Rank (graph theory), Grey relational analysis, Computer science, Set (abstract data type)