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首页> 外文期刊>International journal of intelligent engineering informatics >Unconstrained optimisation through bat algorithm
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Unconstrained optimisation through bat algorithm

机译：通过bat算法进行无约束优化

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摘要

Swarm-based metaheuristic algorithms have bridged the gap from ideal situation to reality. They have been successful in removing the limitations of conventional methods by providing optimal and sub-optimal solutions to those optimisation problems which were earlier considered next to impossible. Their characteristics such as self-organisation and decentralisation have led to these advancements in literature. In this paper, the performance of one such nature inspired algorithm namely the bat algorithm has been tabulated on the basis of precision and convergence speed. The conclusions drawn from the performance and observations are also described later.
机译：基于群体的元启发式算法弥合了从理想情况到现实的鸿沟。通过为那些先前被认为几乎不可能实现的优化问题提供最优和次优解决方案，他们成功地消除了传统方法的局限性。它们的特征如自组织和分散化导致了文学的这些进步。在本文中，已经基于精度和收敛速度将一种此类自然启发算法（即蝙蝠算法）的性能制成表格。从性能和观察得出的结论也将在后面描述。

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