中文摘要：

已有演化元胞遗传算法中的演化规则多从元胞自动机中直接引入，未在状态演化中考虑个体间适应值的差异。根据密度制约关系提出一种新的演化元胞遗传算法来处理动态优化问题，在考虑个体适应值优劣与局部种群密度的前提下，通过密度制约与种内竞争实现个体在元胞空间内的生死演化，并建立种群规模增长模型控制元胞空间内存活个体规模。选取不同强度、复杂度的动态优化问题对算法性能进行验证，结果表明新算法具有良好的处理动态优化问题的能力。

英文摘要：

Among the existing research, most of evolution rules in cellular genetic algorithm （CGA） are di- rectly introduced from cellular automaton. For these evolution rules, the interaction between individuals and the relationship between evolution scheme and group behavior of individuals are ignored. A new evolution CGA based on density dependence scheme is proposed to solve dynamic optimization problems, in which state evolution is achieved by density dependence and intraspecific competition. Moreover, a growth model in fixed cellular space is also proposed to control the population size in the evolutionary process. Dynamic optimization problems with different complexity are selected to verify the algorithm performance. The computation results indicate that the new algorithm has the approving performance in dealing with the dynamic optimization pro- blems.