A genetic algorithm for constrained optimization in simultaneous stabilizing problem

This paper proposes a new constrained optimization algorithm after concisely surveying the constraint handling method in genetic algorithm. Traditional genetic algorithm is improved and the new algorithm is used for solving the simultaneous stabilizing control problem. Some other concepts, either superior to or equivalence to genetic algorithms, are used for comparison. It is shown that the algorithm can systematically handle constraints and it needs neither aiding penalty functions nor feasible initial solutions in producing infeasible solutions. Comparison of experimental results and numerical simulation show that the algorithm has good performance and can effectively solve simultaneous stabilizing problem