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Optimal Design Using Clonal Selection Algorithm

机译:使用克隆选择算法的优化设计

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摘要

In this paper, the Clonal Selection Algorithm (CSA) is employed by the natural immune system to define the basic features of an immune response to an antigenic stimulus. This paper synthesizes the advantages of clonal selection algorithm and proposed optimal design problem using clonal selection algorithm which is a basis of the immune system. CSA, the essence of immune algorithm, is effective to solve optimal problem. The clonal selection algorithm is highly parallel and presents a fine tractability in terms of computational cost. Like the genetic algorithm, clonal selection algorithm is a tool for optimum solution. Clonal selection algorithm and genetic algorithm are used to reach the optimization performances for two numerical function. Then those results are compared each other. These proposed algorithms are shown to be an evolutionary strategy capable of solving optimal design problem.
机译:在本文中,自然免疫系统采用克隆选择算法(CSA)来定义针对抗原刺激的免疫反应的基本特征。本文综合了克隆选择算法的优点,并提出了使用克隆选择算法作为免疫系统基础的最优设计问题。 CSA是免疫算法的本质,可有效解决最优问题。克隆选择算法是高度并行的,并且在计算成本方面具有良好的易处理性。与遗传算法一样,克隆选择算法也是获得最佳解的工具。使用克隆选择算法和遗传算法来达到两个数值函数的优化性能。然后将这些结果相互比较。这些提出的算法被证明是一种能够解决最佳设计问题的进化策略。

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