In this case, the alternatives consist of the algorithms and the criteria are the benchmarks. Since the TOPSIS is not able to handle directly this kind of data, we develop an approach based on TOPSIS for algorithm ranking named as A-TOPSIS. Ranking algorithms, e.g., by means of Friedman test may also present limitations since they consider only the mean value and not the standard deviation of the results. ![]() In order to compare algorithms performance it is very common to handle such issue by means of statistical tests. In evolutionary computation, algorithms are executed several times and then a statistic in terms of mean values and standard deviations are calculated. ![]() In this paper, we propose an alternative novel method based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the problem of ranking and comparing algorithms.
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June 2023
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