Abstract: An adaptive ant colony algorithm is presented for the optimization of multi-minimum continuous function. By dividing the space of solution into subdomains and dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating based on the distribution of the solutions, the algorithm can find the subdomain in which the solution is located, and then determines the specific value of the solution within the subdomain. The simulation results show that the algorithm has many good performances such as avoiding local optimum, high precision solution, quick convergence and good reliability, which are better than those of simple genetic algorithm and clonal selection algorithm.