Quantum Genetic Algorithm Using a Mixed Update Strategy

In order to improve the adaptability of optimization algorithm and solve different types of function optimization problems, a quantum genetic algorithm using a mixed update strategy (MUSQGA) is proposed in this paper. It integrates particle swarm optimization and dynamic rotation gate into the quantum genetic algorithm. In the population each individual utilizes a mixed update strategy to update the angle of quantum rotation gate. To verify the performance of the algorithm, ten representative functions are selected as a testing function set and two groups of comparative experiments are carried out. The experimental results show that MUSQGA is effective and feasible.