Continuous ant algorithm based on cooperation in radar network optimization

From the perspective of deployment features and defense area partition, we establish the static radar network and optimal deployment model, and based on this model, we put forward the issue of high-dimensionally continuous spatial deployment. From the standpoint of ant colony optimization, and aimed at improving Continuous Multi Ant-Colony Optimization (CMACO) in which pheromone is normally distributed, we raise a Algorithm based on cooperation which faces high-dimensionally intelligent optimization. In this method, introduces queue interaction in search of ant colony, connects the mechanism of head ant guide and mass recruitment, and finally realizes cooperated search under high-dimension form. The practice of optimal design shows that this algorithm can be applied into high-dimensional, complex, and much restrained optimal problem, moreover, the optimal time takes less than that of traditional intelligent method, satisfying the warning demand of reentry stage.