A new mutative scale chaos optimization Quantum Genetic Algorithm

Aiming at the trouble of easy getting into local minimum existed in quantum genetic algorithm, this paper presents a new chaos quantum genetic algorithm. This algorithm executes global search using the chaos movementpsilas ergodicity and randomness, and searches the local space of current optimal solutions using the prior knowledge in the process of search and combining the idea of gradient descent, thereby can improve the convergence speed. Adopting the ameliorated mutative scale chaos optimization method, chaotic search for the optimization is implemented to the population that is processed one time with the quantum genetic algorithm, which can lead to the rapid evolution of the population. The test of typical function shows that the performance of this method is better than quantum genetic algorithm and genetic algorithm.