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面向全局优化基于分形的混合混沌优化算法

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Indexed by:期刊论文

Date of Publication:2016-05-08

Journal:数学的实践与认识

Included Journals:PKU、ISTIC

Volume:46

Issue:9

Page Number:192-202

ISSN No.:1000-0984

Key Words:混沌优化算法;分形;共轭梯度法;BFGS算法;Newton-Raphson迭代

Abstract:Julia集具有分形结构,一旦确定吸引域边界上任一点,就可通向任一个吸引周期点的吸引域.Newton-Raphson法利用此性质可计算方程所有根,并可精确计算BFGS法和共轭梯度法中下降方向步长,将两种算法分别与混沌优化算法结合,因而从新的视角建立一种融合分形理论的混合混沌优化算法.研究表明,所提出算法的计算效率高于利用Wolf一维不精确搜索求得步长的混合算法,而且混合混沌BFGS算法的优化能力优于混合混沌共轭梯度算法,也说明BFGS的局部搜索能力比共轭梯度法强.

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