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Abstract. Seven up-to-date adaptive variants of differential evolution were compared in six benchmark problems of two levels of dimension (D = 30 and D = 100). The opposition-based optimization was also implemented to each adaptive variant and compared in experiments. It was found that all the algorithms perform very reliably in the problems of D = 30, whereas their reliability rate in the problems of D = 100 differs substantially among the test problems. Only two algorithms (JADE and b6e6rl variant of competitive DE) operate with acceptable reliability in all the problems. Considering the computational costs, the rank of the algorithms is different in various problems. When the average performance over all the problems is taken into account, JADE was the most efficient and b6e6rl the most reliable. The implementation of opposition-based optimization into adaptive variants of differential evolution does not increase the reliability and its positive influence on the efficiency is rare. Based on the results, recommendations to application of adaptive algorithms are formed and the source code of the algorithms is available online.

A variant of competitive differential evolution modified for the solution of single objective constrained realparameter optimization is presented in this paper. The modification consists in alternation of minimization of the constrains' violation and minimization of objective function value. The variant was tested on the family of 18 problems developed for the Special Session S000 of CEC2010. Using competitive setting avoids tuning of most control-parameter values because only size of population must be set by the user of the algorithm. The experimental results showed acceptable reliability of the search in most of test problems.