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Fast chaotic optimization algorithm based on locally averaged strategy and multifold chaotic attractor

机译:基于局部平均策略和多重混沌吸引子的快速混沌优化算法

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摘要

Recently, chaos theory has been used in the development of novel techniques for global optimization, and particularly, in the specification of chaos optimization algorithms (COAs) based on the use of numerical sequences generated by means of chaotic map. In this paper, we present an improved chaotic optimization algorithm using a new two-dimensional discrete multifold mapping for optimizing nonlinear functions (ICOMM). The proposed method is a powerful optimization technique, which is demonstrated when three nonlinear functions of reference are minimized using the proposed technique.
机译:近来,混沌理论已被用于全局优化的新技术的开发中,尤其是在基于利用混沌图生成的数字序列的混沌优化算法(COA)的规范中。在本文中,我们提出了一种改进的混沌优化算法,该算法使用新的二维离散多重映射来优化非线性函数(ICOMM)。所提出的方法是一种强大的优化技术,当使用所提出的技术最小化三个参考非线性函数时,可以证明这一方法。

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