This paper presents a novel chaotic augmented Lagrange method for solving constrained optimization problems. The algorithm employs chaotic maps to reduce the search space and to get the best parameters for handling the problem constraints. Then, the first carrier wave method can be applied to obtain a solution as an initial point of simplex method to find optimal solution. To verify the efficiency of the proposed algorithm, an empirical study is conducted in three groups: mathematical, challenging, and structural optimization problems. The experimental results show that the proposed method can solve different kinds of constrained optimization problems with great precision.

中文翻译：

---

一种基于混沌的约束优化算法

本文提出了一种解决约束优化问题的新颖的混沌增强拉格朗日方法。该算法采用混沌映射来减少搜索空间并获得用于处理问题约束的最佳参数。然后，可以将第一载波方法应用于获得解，作为单纯形法的起点来找到最佳解。为了验证所提出算法的效率，进行了三组实证研究：数学，挑战性和结构优化问题。实验结果表明，该方法可以很好地解决各种约束优化问题。