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A Spatially Informative Optic Flow Model of Bee Colony With Saccadic Flight Strategy for Global Optimization

机译:全局优化的蜂群空间信息流模型及跳频飞行策略

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This paper presents a novel search metaheuristic inspired from the physical interpretation of the optic flow of information in honeybees about the spatial surroundings that help them orient themselves and navigate through search space while foraging. The interpreted behavior combined with the minimal foraging is simulated by the artificial bee colony algorithm to develop a robust search technique that exhibits elevated performance in multidimensional objective space. Through detailed experimental study and rigorous analysis, we highlight the statistical superiority enjoyed by our algorithm over a wide variety of functions as compared to some highly competitive state-of-the-art methods.
机译:本文介绍了一种新颖的搜索元启发式方法,其灵感来自对蜜蜂有关空间环境信息流的物理解释的物理解释,这些信息有助于它们定向自己并在觅食时在搜索空间中导航。通过人工蜂群算法对解释的行为与最小的觅食行为进行了组合,以开发一种鲁棒的搜索技术,该技术在多维目标空间中表现出较高的性能。通过详细的实验研究和严格的分析,我们强调了与某些竞争激烈的最新方法相比,我们的算法在多种功能上的统计优势。

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