电子学报 ›› 2013, Vol. 41 ›› Issue (12): 2468-2473.DOI: 10.3969/j.issn.0372-2112.2013.12.023

• 科研通信 • 上一篇    下一篇

多尺度量子谐振子高维函数全局优化算法

王鹏1, 黄焱2,3, 任超1, 郭又铭2,3   

  1. 1. 成都信息工程学院并行计算实验室, 四川成都 610225;
    2. 中国科学院成都计算机应用研究所, 四川成都 610041;
    3. 中国科学院大学, 北京 100049
  • 收稿日期:2012-08-21 修回日期:2013-03-06 出版日期:2013-12-25
    • 通讯作者:
    • 王鹏
    • 作者简介:
    • 黄 焱 男,1982年7月出生于江苏省泗阳县.博士研究生.主要研究方向为智能算法、云计算、并行计算. E-mail:16481339@qq.com
    • 基金资助:
    • 国家自然科学基金基金 (No.60702075); 广东省科技厅高新技术产业化科技攻关项目 (No.2011B010200007); 四川省青年科学基金 (No.09ZQ026-068); 成都市科技局创新发展战略研究项目 (No.11RXYB016ZF)

Multi-Scale Quantum Harmonic Oscillator for High-Dimensional Function Global Optimization Algorithm

WANG Peng1, HUANG Yan2,3, REN Chao1, GUO You-ming2,3   

  1. 1. Parallel Computing Laboratory, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China;
    2. Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China;
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-08-21 Revised:2013-03-06 Online:2013-12-25 Published:2013-12-25

摘要: 函数优化问题与量子谐振子从高能态向基态收敛过程具有相似的概率解释,结合基于高斯尺度函数的多尺度二进信息采样方法,提出了高维函数优化问题的多尺度量子谐振子算法模型,该算法模型将高维函数优化过程分为尺度收敛和量子谐振子收敛两个步骤,物理模型明确,无需编码和复杂的初始条件设定,即可实现高维函数优化.通过对15种典型二维优化测试函数和6种典型的高维优化测试函数进行实验和分析表明,多尺度量子谐振子算法可以快速精确地获得高维函数的全局最优解,同时采用“降频”方法可以提高对具有“高频”成分函数的搜索速度.

关键词: 多尺度量子谐振子算法, 波函数, 函数优化, 全局优化

Abstract: With the multi-scale binary sampling methods on the basis of Gaussian scaling function,the model of multi-scale quantum harmonic oscillator algorithm for high-dimensional function global optimization problems is proposed.High-dimensional function optimization process is divided into two steps,scale convergence and quantum harmonic oscillator convergence.This algorithm model is based on the same convergence process probability interpretations between function optimization problem and quantum harmonic oscillator from high-energy state to ground state.This algorithm,which has explicit physical model,can realize high-dimensional function optimization without coding or complex initial conditions.Experiments and analysis are done for 15 typical two-dimensional optimized test functions and 6 typical high-dimensional optimized test functions.The results show that multi-scale quantum harmonic oscillator algorithm gets precise global optimum for high-dimensional function quickly,and with "reduced frequency"approach,the search speed of function with "high frequency" component improves significantly.

Key words: multi-scale quantum harmonic oscillator algorithm, wave function, function optimization, global optimization

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