The Improvement Clone Selection Algorithms And Their Application

Biological immune system is a highly parallel adaptive information learning system, which can identify and remove the antigenic eye winkers invading the body. This system can learn, remember and adjust adaptively to keep the stabilization inside the body. During recent years, people begin to realize the revelatory significance of the biological immune mechanism to intelligent algorithm. Clone selection algorithm is this kind of new algorithm which is inspired by the biological immune system. It can be said that, nowadays the study of artificial immune algorithm combines two main features, the priory knowledge and the adaptive ability of immune system, endowing it with powerful and robust ability, which can deal with information .It is considered to be a very significant and meaningful research direction. Now this kind of algorithm has been used in many fields, such as pattern recognition, unconventionality and malfunction diagnosis, control of robots, in break detection of network, function optimization and etc. By using the priority of the artificial immune algorithm.On the analysis of the clone selection mechanism, studying the application of the algorithm which used in multi-modal function and dynamic routing optimum in this paper.The main work as follows:(1) The origin, systematic function and basic concepts of the biological immune system are introduced, immune mechanism, optimum mechanism and the main immune optimization algorithm of artificial immune system are simply introduced. Then, the basic principle, features and the application of clone selection algorithm are also presented.(2) On the analysis of the insufficient of the classic CLONALG algorithm, with the improvement of operation of clone selection ,clone mutation and the operation of antibody suppression is introduced, a advanced Clone selection Algorithm is proposed. And the result of the optimization of the algorithm for multi-modal function has been compared with CLONALG and opt-aiNet.(3) On the analysis of traveler's selection for the optimum routing represent multi-objective characteristic, and traveler could adjust the previous routing based on traffic status, a multi-objective model of dynamic routing based on link travel time and link length is presented. Then, a Clone Selection Algorithm solving the model is put forward, with analysis the encoding method and the operation of mutation. Simulation results show that the algorithm is efficient and has the characteristic of real-time performance, could also provide the optimum routing on the basis of real-time traffic information.