A hybrid algorithm integrating the clone selection algorithm with the ant colony algorithm by adaptive fusion
(ACALA) based on local optimization search strategy is proposed. In order to increase the diversity of the antibody and improve the search capabilities of ant algorithm, a mechanism of chaotic disturbance is introduced into this algorithm. The operation of clone expansion, immune gene, etc is adopted to enhanced the variety of antibody and affinity maturation. The adaptive control parameter is used to achieve the purpose of integrating the clone selection algorithm with the ant colony algorithm organically. Simultaneously, the proposed hybrid algorithm can prevent premature convergence effectively by taking advantage of local optimization search strategy. The results of the experiments on travelling salesman problems (TSP) show that the proposed algorithm can improve the search performance significantly no matter in convergent speed or precision.