Quantum Evolutionary Algorithm And Its Application

The 20th century is a resplendent age with an all-time development of technology and civilization. Computers centered Modern Information Processing and digital information characterized Modern Information Transmission are in process of their close combination. As an active research direction of intelligent information processing, computational intelligence (CI) has attracted many scientists' attention. In recent years, CI is generally considered as a new computational method based on the full development of its three branches－Neural Network(NN), Fuzzy System(FS) and Evolutionary Computation(EC). In fact, CI includes abundant implications. Over a long period, the worldwide researchers are going in different directions and using various methods to approach the essence of CI. Naturally, CI is an abstract subject spanning Physics, Mathematics, Computer Science, Communication, Physiology, Evolution and Psychology. Accordingly, using the extracted knowledge of these subjects can make a deeper investigation into CI and give a basis for the optimization, also help to build up a more uniformly intelligent method of system design. In this paper, a frame of quantum evolutionary algorithm is presented by the combining of quantum theory with evolutionary theory. Its algorithms are given in detail and their convergences are proved. Both the theory analysis and simulations prove its superiority. The content of this paper includes: ● Give an introduction about the recent development of the quantum computation in the researches of computation intelligence ● A frame of quantum evolutionary algorithm is presented ● An optimal MUD based on a quantum evolutionary algorithm is presented ● A discrete particle swarm optimization based on quantum individual is presented...