计算机科学 ›› 2019, Vol. 46 ›› Issue (8): 266-271.doi: 10.11896/j.issn.1002-137X.2019.08.044

• 人工智能 • 上一篇    下一篇

基于MQHOA优化算法的尺度变化行为

周岩1, 王鹏1, 辛罡2,3, 李波2,3   

  1. (西南民族大学计算机科学与技术学院 成都610225)1
    (中国科学院成都计算机应用研究所 成都610041)2
    (中国科学院大学 北京100049)3
  • 收稿日期:2018-07-20 出版日期:2019-08-15 发布日期:2019-08-15
  • 通讯作者: 王鹏(1975-),男,博士,教授,CCF会员,主要研究方向为云计算、并行计算、量子算法,E-mail:wp002005@163.com
  • 作者简介:周岩(1976-),男,硕士生,主要研究方向为云计算、并行计算、量子算法;辛罡(1983-),男,博士生,主要研究方向为云计算、量子算法;李波(1980-),男,博士生,主要研究方向为云计算、量子算法
  • 基金资助:
    国家自然科学基金资助项目(60702075),国家自然科学基金面上项目(71673032),四川省教育厅2018一般项目(18ZB0623),西南民族大学中央高校基本科研业务费专项资金项目(2019NYB22)

Scale Change Based on MQHOA Optimization Algorithm

ZHOU Yan1, WANG Peng1, XIN Gang2,3, LI Bo2,3   

  1. (School of Computer Science and Technology,Southwest Minzu University,Chengdu 610225,China)1
    (Chengdu Institute of Computer Application,Chinese Academy of Sciences,Chengdu 610041,China)2
    (University of Chinese Academy of Sciences,Beijing 100049,China)3
  • Received:2018-07-20 Online:2019-08-15 Published:2019-08-15

摘要: 尺度收敛是智能优化算法求解过程的重要环节,不确定性原理和量子隧道效应佐证了这一重要性。在多尺度量子谐振子算法(Multi-scale Quantum Harmonic Oscillator Algorithm,MQHOA)的优化迭代过程中,通过调整尺度收敛幅度,能够影响算法的求解效果和运算性能。对尺度变化进行研究,定义函数在2维状态下对应的最佳尺度收敛参数为该函数的尺度系数(Scale Factor,SF)。尺度系数可以作为衡量函数尺度结构复杂程度的定性判据参考,能够协助算法针对不同函数采用最合适的收敛尺度来寻求最优解。

关键词: 尺度收敛, 多尺度量子谐振子算法(MQHOA), 优化算法

Abstract: Scale convergence is an important part of the computational process of intelligent optimization algorithm.The uncertainty principle and quantum tunneling effect prove this importance.In the optimization iterative process of the multi-scale quantum harmonic oscillator algorithm (MQHOA),by adjusting the scale convergence range,the algorithm’ssolution effect and computational performance can be affected.The scale variation was studied,and the optimal scale convergence parameter corresponding to the function in the 2-dimensional state was defined as the scale factor of the function.The scale factor can be used as a qualitative criterion for measuring the complexity of the function scale structure.The scale factor can help the algorithm to find the optimal solution by using the most suitable convergence scale for different functions

Key words: Multi-scale quantum harmonic oscillator algorithm, Optimization algorithm, Scale convergence

中图分类号: 

  • TP301.6
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