Abstract Ant colony optimization algorithm is a new simulated evolutionary algorithm, which has the faculty of global optimization. An adaptive parallel ant colony optimization algorithm (APACO) is presented. It dynamically adjusts the parameters according to the searching phases, thus the convergence is accelerated to a certain extent. The adaptive migration rule could not only enrich the diversity of the colonies but also reduce the communication between colonies. Finally, the CHN144 problem of China in Nonnumerical Parallel Algorithm: the Simulated Annealing Algorithm by Lishan Kang is applied to calibrate the algorithm. Results show that the proposed algorithm improves the searching speed with good global convergence.
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2007, Vol. 20 
