Abstract
Danger Model Immune Algorithm (DMIA) is an algorithm based on the danger theory of biological immunology. In the framework of the algorithm, the danger area is fixed in the process of optimization. In this paper, an improved algorithm is proposed which are different from the framework of the algorithm. In the new algorithm, the danger area will be changed gradually according to the iterations automatically. And two kinds of method (linear and nonlinear) are adopted to adjust the danger area. Complex function is used to test the algorithm. Through the comparison test, the results denote that the nonlinear method is more effective than the linear one, and has better optimization capability.
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