Abstract
Clonal Selection Algorithm (CSA) has been applied widely in intelligent computation field, but the global convergence theoretical analysis and research works about CSA were rare relatively. The global convergence of an improved clonal selection algorithm is investigated in this paper. Through the definition of global convergence in probability, the classical homogeneous Markov chain analyses is replaced by a new pure probability and iterative formula method, and the convergence results of the improved clonal selection algorithm are obtained. This method makes the global convergence research greatly simplified and enriches new contents for the theoretical foundation of the clonal selection algorithm.
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