Abstract: Aimed at the shortcomings of genetic algorithm (GA) and ant colony algorithm (ACA), an improved genetic ant colony hybrid algorithm is presented. By determining the improved situation of the optimal solution, the hybird algorithm actualizes dynamic serial fusion for GA and ACA, which makes full use of global search ability of GA and positive feedback mechanism of ACA. Meanwhile, according as the importance of pheromone in positive feedback process, an improved pheromone update mechanism with encouragement or penalty item is proposed. Computing simulation examples show the hybrid algorithm is of much higher convergence speed and much better quality of solutions than that of classical GA or ACA.
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