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A simple framework for cooperation of evolutionary algorithms in the solution of constrained optimization problems is proposed and implemented using two advanced adaptive variants of differential evolution. The new algorithm is applied to the test problems defined for CEC 2017 competition on constrained single objective real-parameter optimization. The new algorithm finds acceptable solution in 75...
Application of differential evolution (DE) to the constrained optimization problems is addressed. A self-adaptive competitive variant of DE with enhanced search for feasibility region is used. The influence of different kinds of mutation (rand/1/, randrl/1/, current-to rand/1/, and a search strategy combing two types of mutation) on the performance is studied. Experimental comparison of four novel...
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