Hybrid Genetic Algorithm for Constrained Nonlinear Optimization Problems

In this paper we present a hybrid optimization algorithm for solving constrained nonlinear optimization problems. The hybrid algorithm is a combination between one of the intelligence techniques (genetic algorithm) and chaos theory to enhance the performance and to reach the optimal solution. The proposed algorithm is operates in two phases: in the first one, genetic algorithm is implemented to solve nonlinear optimization problem. Then, in the second phase, local search referred to chaos theory is introduced to improve the solution quality and find the optimal solution. The results of numerical studies have been demonstrated the superiority of the proposed approach to finding the global optimal solution.