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  • Anyong Qing
  • 2008 IEEE Congress on Evolutionary Computation…
  • 2008
One of the keys leading to the success of differential evolution is its mechanism of differential mutation for generating mutant vectors. In the community of differential evolution, the mutation operator is usually marked as x/y where x indicates how the base vector is chosen and y (ges1) is the number of vector differences added to the base vector. It is(More)
In order to understand the role of crossover in differential evolution, theoretical analysis and comparative study of crossover in differential evolution are presented in this paper. Two new crossover methods, namely consecutive binomial crossover and non-consecutive exponential crossover, are designed. The probability distribution and expectation of(More)
The differential evolution (DE) algorithm with a new differential mutation base strategy, namely best of random, is applied to the synthesis of unequally spaced antenna arrays. In the best of random mutation strategy, the best individual among three randomly chosen individuals is used as the mutation base while the other two are for the vector difference.(More)
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