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Exponentially decreased dimension number strategy based dynamic search fireworks algorithm for solving CEC2015 competition problems

机译:基于指数降维策略的动态搜索烟花算法解决CEC2015竞争问题

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Fireworks algorithm (FWA) is one swarm intelligence algorithm proposed in 2010, which takes the inspiration from the firework explosion process. Compared with other meta-heuristic algorithms, FWA presents a cooperative explosive search manner. In the explosive search manner, the explosion amplitudes, explosion sparks' numbers and explosion dimension selection methods play the key roles for its successful implementation. In this paper, the performance analyses of the different explosion dimension number strategies in FWA and its variants are presented at first, then the exponentially decreased explosion dimension number strategy is introduced for the most recent dynamic search fireworks algorithm (dynFWA), called ed-dynFWA, to enhance its local search ability. To validate the performance of ed-dynFWA, it is used to participate in the CEC 2015 competition for solving learning based optimization problems.
机译:烟花算法(FWA)是2010年提出的一种群智能算法,其灵感来自烟花爆炸过程。与其他元启发式算法相比,FWA提出了一种协同爆炸搜索方式。以爆炸物搜索的方式,爆炸幅度,爆炸火花数和爆炸尺寸选择方法是成功实施爆炸物的关键。本文首先介绍了FWA及其变种中不同爆炸维数策略的性能分析,然后针对最近称为ed-dynFWA的最新动态搜索烟花算法(dynFWA)引入了按指数递减的爆炸维数策略。 ,以增强其本地搜索能力。为了验证ed-dynFWA的性能,它被用来参加CEC 2015竞赛,以解决基于学习的优化问题。

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