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An Improved Immune Genetic Algorithm Based on Niche Algorithm and Its Application

机译:一种基于小生境算法的改进的免疫遗传算法及其应用

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In order to overcome traditional genetic algorithm (GA)'s deficiency of slow convergence, and Niche algorithm's too fast convergence, this paper presents a new Improved Immune Genetic Algorithm (IIGA) based on the improved Niche algorithm. Firstly, the improved Niche algorithm, including convergence function, and "noise" chromosome, is given. Then based on the proposed flowchart of IIGA, the steps of the algorithm are introduced in detail. Finally, the IIGA is exemplified, and proved to be feasible and effective by comparing with self-adaptive Genetic Algorithm(SAGA) and traditional GA.
机译:为了克服传统遗传算法收敛速度慢和Niche算法收敛速度太快的不足,提出了一种基于改进的Niche算法的改进的免疫遗传算法。首先,给出了改进的Niche算法,包括收敛函数和“噪声”染色体。然后根据提出的IIGA流程图,详细介绍了该算法的步骤。最后,通过与自适应遗传算法(SAGA)和传统遗传算法进行比较,以IIGA为例进行了验证,证明了该算法的可行性和有效性。

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