This paper proposes the real-coded distributed clonal selection algorithm (DCSA) for use in electromagnetic design optimization. This algorithm employs different types of probability distributions for the mutation of the clones. In order to illustrate the efficiency of this algorithm in practical optimization problems, we compare the results obtained by DCSA with other immune and genetic algorithms over analytical problems and for the TEAM Workshop Problem 22 for the 3 and 8 variables versions. The results indicate that the DCSA is a suitable optimization tool in terms of accuracy and performance.
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Batista et al. (2009) studied this question.
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