Research On Artificial Immune Algorithm For Solving Function Optimization Problems

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. Artificial immune algorithm is this kind of new algorithm which is inspired by the biological immune system. Nevertheless, the complication of the immune system force the study of artificial immune algorithm hasn't attached enough development applications over internal and external are relatively less. 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 machine learing, unconventionality and malfunction diagnosis, simulation of the behavior of robots, control of robots, in break detection of network, function optimization and etc. By using the priority of the artificial immune algorithm, we gain the improving multi-peak algorithm which can effectively solve the function optimization problems,the main work as follows: (l)The basic concepts framework functions and principles of the biological immune system are introduced ,the research fields .research status and basic theory of the genetic algorithm and artificial immune system are simply analyzed.(2) Comparing with each artificial immune algorithm on the base of systematizing study on the existing artificial immune algorithm, it develops the memory cell's function into an important component part of algorithm through the progressive research on the biological immune systematizing mechanism ,and takes fully use of the Baldwin Effect of the biological immune system, works out the improving multi-peak value artificial immune algorithm.(3) Through an emulative case, multi-peak value artificial immune algorithm provesits effectiveness and well robustness. At the same time, the essay amends the arithmetic operator in the original algorithm, and applies it in the new algorithm, improves the global search ability and convergence rates in a great deal. The good result demonstrates that the algorithm on solving the function optimization problem is a kind of feasible and good new method.