进化算法在大规模优化问题中的应用综述
A Survey of Evolutionary Algorithms for Large Scale Optimization Problem

针对大规模问题的特点，对已有的大规模优化算法进行了简单的分析.主要介绍算法的初始化方法、不分组策略、静态分组策略、动态分组策略、自适应分组策略、大规模优化算法测试函数集以及算法结果的对比等方面；侧重描述优化算法的搜索策略、更新策略、突变策略和协同进化策略，并列出大规模优化算法测试函数集的特点及优化算法的评价方法；最后，给出了目前大规模优化问题的几个研究难点。
Based on the characterisities of large-scale problems, lager-scale optimization were grossly analyzed. This paper introduced some methods for lager-scale problems.The methods included the initialization method, decomposition strategy, updating strategy and so on. This paper mainly focued on the search strategy, update strategy, mutation strategy and cooperative coevolution. Meanwhile, the characteristics of lager-scale optimization algorithm testing function set and evaluation method were listed. Finally, the future research directions were given.