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An Improved Bio-inspired BAT Algorithm for Optimization

机译:一种改进的生物启发蝙蝠算法优化

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Metaheuristic algorithms are used today to solve many optimization-related problems. The firefly algorithm, particle swarm optimization, harmony search and BAT algorithm are used as metaheuristic searched algorithms to find the optimized solution of the problem domain. The BAT algorithm was developed by using the unique characteristics of BAT which used the advanced capability of echolocation to move in the dark, avoid obstacles or barrier and also find its food or pray. The main aim of this paper is to represent and translate the behaviour of BAT algorithm in the form of improved BAT algorithm. The paper also describes the implication, advantage, disadvantage and application of BAT algorithm in different areas used by diversified authors.
机译:今天使用了所遗传算法来解决许多优化相关的问题。 Firefly算法,粒子群优化,和声搜索和BAT算法用作元培养搜索的算法,以找到问题域的优化解决方案。 通过使用利用eCholocation的先进能力在黑暗中移动的蝙蝠的独特特性开发了BAT算法,避免了障碍物或障碍物,也找到了食物或祈祷。 本文的主要目的是以改进的BAT算法形式代表和翻译BAT算法的行为。 本文还介绍了多样化作者使用的不同区域中BAT算法的含义,优势,缺点和应用。

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