Constantin URSACHE, Florina ȘERDEAN, Lucian TUDOSE


This paper presents a comparative study between a traditional evolutionary algorithm with the values of the parameters set before the algorithm runs and that remain fixed during runtime, and a cultural algorithm using parameter control powered by Lévy flight to dynamically update the values of the parameters during runtime. The two algorithms are benchmarked on a subset of test problems, using an open-source platform for comparing continuous optimizers in a black box setting. The results obtained are examined in order to demonstrate the improved performance of the cultural algorithm using parameter control, its superiority becoming more evident as the dimensions of the test problems increase.

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