Abstract
This paper proposes a novel hybrid immune clonal selection algorithm coupling with multi-parent crossover and chaos mutation (CSACC). CSACC takes advantages of the clonal selection mechanism and the learning capability of the clonal selection alorithm (CLONALG). By introducing the multi-parent crossover and neighbourhood mutation operator, CSACC achieves a dynamic balance between exploration and exploitation. And by using the characteristics of ergodicity and dynamic of chaos variables, the chaotic optimization mechanism is introduced into CLONALG to improve its search efficiency. The experimental results on function optimization show that the hybrid algorithm is more efficient than the clonal selection algorithm.
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