A novel cellular genetic algorithm with predator and prey mechanism is proposed in this paper to improve the ability of escaping from premature trap. To mimic the predator-prey model in the natural ecology, the evolution rule of cellular genetic algorithm is replaced with a predator and prey mechanism. Whether the individual can survive is decided not only by the fitness of predator and prey, but also by the density of the predators and preys in the neighborhood. The population size of predator and prey individuals is maintained in a reasonable range by a certain population size control strategy. The predator and prey mechanism balances the tradeoff between exploration and exploitation. In an experiment of optimization of several typical complicated
functions, the proposed algorithm shows better performance in avoiding premature trapping, and can obtain higher convergence rate of global optimum.
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