求解约束非线性优化问题的群体复合形进化算法

分析了SCE－UA算法的特性，指出该算法仍存在着一些缺陷，例如（1）SCE－UA算法的全局最优性依赖于随机选取的初始点集的多样性，若初始点集选取不当，搜索进化就会早熟而陷入局部最优解；（2）SCE－UA算法其求解效率有待于进一步提高，提出了群体复合形进化算法，能充分利用目标函数值的信息，优化搜索过程具有较强的方向性和目标性，收敛速度较快，且是全局优化算法，能有效地求解不等式约束非线性优化问题。

Multi-Complex Evolution Algorithm for Constraint Nonlinear Optimization Problems

The essential concepts and the characters of the SCE UA method are reviewed, and some limitations of the SCE UA method are pointed out, such as (1) the global optimum of the method depends on the variety of the initial point sets, if the initial point sets can not be selected properly, the global optimum can not be obtained,(2) the general inequality constraint nonlinear optimization problems can not be solved effectively. In this paper, a more effective method called Multi Complex Evolution Algorithm for Constraint Nonlinear Optimization Problems is presented. This new method can use the information of the objective function to search for the optimum objectively. This new method is a global optimization method,which can be used for general inequality constraint nonlinear optimization problems efficiently and effectively.