constrained optimization; differential evolution; feasibility region; opposition-based optimization; controlled random search

Application of competitive differential evolution (DE) with enhanced search for feasibility region is addressed. Influence of different kinds of mutation is investigated by comparison on the benchmark set developed for the special session of IEEE Congress of Evolutionary Computation (CEC) 2010. The experimental results showed that tested variants of competitive DE using different kinds of mutation perform almost equally and there is no significant influence of the kind of mutation on the overall feasibility rate. Some tested competitive DE variants performed equally or even better when comparing with the best algorithm of CEC 2010 competition in several benchmark problems.