Abstract: This paper proposes a new self-adaptive Multi-Parent Crossover evolutionary algorithm based on Gaussian and Cauchy mutation for solving constrained function optimization problems.The specialty of the algorithm include： using three novel multi-parent crossover operators which can speed up the constringency dramatically；introducing a new method based on Gaussian and Cauchy mutation for producing the new individual；introducing a self-adaptive mechanism to adjust the dimension of the search subspace as the searching range changed.This paper presents some results of numerical experiments which show the new algorithm is more universal，effective and robust than its competitors，especially the constringency and stability.

Key words: evolutionary algorithm, Gaussian and Cauchy mutations, multi-parent crossover, self-adaptive methods

摘要： 提出一种基于高斯柯西变异算子的多父体杂交自适应演化算法，并用于求解约束函数优化问题。算法的特点：在随机搜索过程中引入三种新的多父体杂交算子加速收敛；基于高斯柯西变异算子提出一种新的产生新个体的方法；提出一种根据演化的进度能自动调整搜索范围的自适应机制。分析与实验表明，与其他算法相比，算法更具有通用性、高效性、鲁棒性，算法收敛速度和算法稳定性有明显改进。

关键词: 演化算法, 高斯柯西变异, 多父体杂交, 自适应机制