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The optimization of a microwave circuit is a complex multi-objective problem (MOP) needed to be effectively solved. Multi-objective evolution algorithms (MOEAs) are efficient in dealing with MOPs because of their population property inspired by the natural evolution of species. Exploitation and exploration are of equal importance to MOEAs for approximating the optimal Pareto front (PF) well. However,...
Differential evolution (DE) is a simple yet powerful evolutionary algorithm for both single objective and multiobjective optimizations (MOPs). In nature, good parents are more likely to produce good offspring, because genes from good individuals propagate throughout the population. Inspired by this phenomenon, a two-step subpopulation strategy is proposed, in which individuals in the current population...
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