中文摘要：

合作型协同进化遗传算法是多个子种群通过协作而共同进化的新型算法,常应用于多目标、大规模的优化问题。本文在合作型协同进化遗传算法的基础上,进一步模拟自然界中的灾变现象,在原先的算法中加入灾变算子,提出灾变合作型协同进化遗传算法,以防止出现不成熟收敛现象,并用经典的函数优化问题和Job Shop车间调度问题进行仿真实验,其结果验证了改进算法的优良性能.

英文摘要：

Cooperative Coevolutionary Genetic Algorithm （CCGA） is a new algorithm in which the sub-populations coevolve through the cooperation of interactional individuals. CCGA is often used in the multi-object problems and the optimizations with large dimensions. On the basis of CCGA,Cooperative Coevolutionary Genetic Algorithm with Catastrophe （CCGA-C） is proposed, in which a catastrophe operation is introduced to simulate the disaster in nature. This new algorithm effectively solves the premature convergence problem and improves the performance of optimization. The experiments of the classical functions optimizations and Job-Shop Scheduling Problem （JSP） optimizations are presented using CCGA-C. The results validate the efficiency of the new algorithm presented in this paper.