提出了一种基于捕食机制的元胞遗传算法，当优化复杂多模函数时，该算法进一步提高了全局探索能力.算法通过模拟生态系统捕食与被捕食之间的相互关系，采用捕食机制替代元胞遗传算法中的演化规则，使得遗传个体生存与死亡状态的演化既与其适应度相关，又与邻域内捕食及被捕食个体密度相关，并通过群体规模控制策略维持捕食与被捕食群体间的个体数目动态平衡，实现了全局搜索与局部寻优之间更好的协调与均衡. 对典型的多峰函数进行优化的实验结果表明，该算法在抑制早熟收敛以及提高全局收敛率方面获得了明显的优势.
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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