Study on mutative scale chaos optimization strategy of quantum genetic algorithm

Aiming at the trouble of easy getting into local minimum and premature convergency existed in quantum genetic algorithm,this paper analysed the flow of QGA,improved the strategy in two sides of global searching and local searching,and presented a new algorithm.This algorithm executed global search using the chaos movement's ergodicity and randomness,in the same time optimized the renovation process of quantum with the gradient information.The test of typical function shows that the performance of this kind of method is better than quantum genetic algorithm and genetic algorithm.