A chaos-based constrained optimization algorithm

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.