Enhanced Competitive Differential Evolution for Co
2016-08-23
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The constrained optimization with differential evolution (DE) is addressed. A novel variant of competitive differential
evolution with a hybridized search of feasibility region is proposed, where opposition-based optimization and adaptive
controlled random search are combined. Various variants of the algorithm are experimentally compared on the benchmark set
developed for the special session of IEEE Congress of Evolutionary Computation (CEC) 2010. The results of the enhanced
competitive DE show effective search of feasible solutions, in difficult problems significantly better than the competitive DE
variant presented at CEC 2010.
evolution with a hybridized search of feasibility region is proposed, where opposition-based optimization and adaptive
controlled random search are combined. Various variants of the algorithm are experimentally compared on the benchmark set
developed for the special session of IEEE Congress of Evolutionary Computation (CEC) 2010. The results of the enhanced
competitive DE show effective search of feasible solutions, in difficult problems significantly better than the competitive DE
variant presented at CEC 2010.
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