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Firefly Algorithm and Grey Wolf Optimizer for Constrained Real-Parameter Optimization

机译:萤火虫算法和灰狼优化器,用于约束真实参数优化

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The main goal of this paper is to present the performance of two popular algorithms, the first is the Firefly Algorithm (FA) and the second one is the Grey Wolf Optimizer (GWO) algorithm for complex problems. In this case the problems that we are presenting are of the CEC 2017 Competition on Constrained Real-Parameter Optimization in order to realize a brief analysis, study and comparison between the FA and GWO algorithms respectively.
机译:本文的主要目标是呈现两个流行算法的性能,第一是萤火虫算法(FA),第二个是灰狼优化器(GWO)算法复杂问题。在这种情况下,我们所呈现的问题是CEC 2017竞争受约束的实际参数优化,以便分别意识到FA和GWO算法之间的简要分析,研究和比较。

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