Analysis of an optimizer based on piecewise-rotational chaotic system
Analysis of an optimizer based on piecewise-rotational chaotic system
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DOI：
10.1587/nolta.7.557
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Yoshikazu Yamanaka;T. Tsubone
中科院分区：
文献类型：
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作者：
Yoshikazu Yamanaka;T. Tsubone
提出了一种基于分段旋转混沌系统的优化方法。OPRC是一种多点搜索方法，通过分段旋转混沌动力学对搜索点进行更新，以求得到最优解。OPRC是一个简单的优化器，因为这些搜索点由不包含随机项的简单动态控制。OPRC的性能明显优于粒子群算法和我们之前的基于另一个混沌系统的方法。分析了OPRC的性能与所提出的混沌系统时间序列的关系。然后阐明了当时间序列的自相关系数为负值时，当时间序列具有衰减振荡时，OPRC得到了较好的解。
An optimization method based on piecewise-rotational chaotic system (OPRC) is proposed. OPRC is a kind of multi-point searching methods in order to find an optimal solution, and these searching points are updated by piecewise-rotational chaotic dynamics. OPRC is a simple optimizer because these searching points are governed by simple dynamics which contains no stochastic terms. OPRC has significantly better performance than particle swarm optimization and our previous method based on another chaotic system. The relationship between the performance of OPRC and the time-series of the proposed chaotic system is analyzed. Then we clarify that OPRC obtains better solutions when the autocorrelation of the time-series takes negative values with damped oscillation.