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A gravitational search algorithm with hierarchy and distributed framework

机译:具有层次结构和分布式框架的引力搜索算法

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Gravitational search algorithm is an effective population-based algorithm. It simulates the law of gravity to implement the interaction among particles. Although it can effectively optimize many problems, it generally suffers from premature convergence and low search capability. To address these limitations, a gravitational search algorithm with hierarchy and distributed framework is proposed. A distributed framework randomly groups several subpopulations and a three-layered hierarchy manages them. Communication among subpopulations finally enhances the search performance. Experiments discuss parameters and strategies of the proposed algorithm. Comparison between it and sixteen stateof-the-art algorithms demonstrates its superior performance. It also shows the practicality for two real-world optimization problems. (c) 2021 Elsevier B.V. All rights reserved.
机译:引力搜索算法是一种有效的基于人群的算法。 它模拟了重力定律,以实现粒子之间的相互作用。 虽然它可以有效优化许多问题,但它通常存在早熟的收敛和低搜索能力。 为了解决这些限制,提出了一种具有层次结构和分布式框架的引力搜索算法。 分布式框架随机组分组多个子步骤和三层层次结构管理它们。 亚步骤之间的通信最终增强了搜索性能。 实验讨论所提出的算法的参数和策略。 它与十六个议定团之间的比较 - 现有技术算法展示了其优越的性能。 它还显示了两个真实世界优化问题的实用性。 (c)2021 elestvier b.v.保留所有权利。

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