Inner-Outer Array Based on Genetic Algorithm With Constraint Relaxation for Constrained Integer Optimization Engineering Problems

The Inner-Outer Array (IOA) and Constraint Relaxation method (CR) are introduced into Genetic Algorithm (GA) to propose hybrid Inner-Outer Array based on Genetic Algorithm with Constraint Relaxation (IOA-GA-CR) for solving hard-to-solve problems. This hybridized approach's search method uses IOA to roughly scan the entire search domain before concentrating the search, using GA, on the promising regions. Combining the IOA and GA algorithms balances the powers of exploration and exploitation, increasing the efficiency of finding global or nearly global optima. The adaptive control parameters of GA are neglected, in this proposed technique, which is reflecting the robustness of the proposed algorithm. Moreover, CR is utilized to block ineffective constraints, turning difficult problems into handled ones. The efficacy of the suggested IOA-GA-CR algorithm is verified through two complicated integer engineering design challenges, then compared to well-known global optimization algorithms. The experimental results show that IOA-GA-CR has a good computational effort and convergence.