MQHOA algorithm with energy level stabilizing process

Peng WANG; Yan HUANG

doi:10.11959/j.issn.1000-436x.2016136

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MQHOA algorithm with energy level stabilizing process

Academic paper | 更新时间：2024-06-05

- MQHOA algorithm with energy level stabilizing process
- Journal of Communications Vol. 37, Issue 7, Pages: 79-86(2016)
- 作者机构：
  
  1. 西南民族大学计算机科学与技术学院，四川成都 610225
  2. 淮阴师范学院计算机科学与技术学院，江苏淮安 223300
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(60702075);Sichuan Key Laboratory Open Foundation of Pattern Recognition and Intelligent Information Processing(MSSB-2015-9)
- DOI：10.11959/j.issn.1000-436x.2016136
  CLC： TP301.6
- Online First：2016-07，
  
  Published：25 July 2016
- 稿件说明：
移动端阅览
Peng WANG, Yan HUANG. MQHOA algorithm with energy level stabilizing process[J]. Journal of Communications, 2016, 37(7): 79-86.
DOI：

Peng WANG, Yan HUANG. MQHOA algorithm with energy level stabilizing process[J]. Journal of Communications, 2016, 37(7): 79-86. DOI： 10.11959/j.issn.1000-436x.2016136.

摘要

在量子模型下将优化问题转化为求解约束态的基态波函数问题，通过泰勒近似采用谐振子势阱对目标函数进行逼近，类比量子谐振子的波函数图像提出了一种改进的多尺度量子谐振子优化算法。算法包括3个基本迭代收敛过程：能级稳定过程、能级降低过程和尺度降低过程，算法的收敛过程与物理模型基本吻合。改进算法将主观控制参数减少为1个，同时参照量子模型定义了算法的波函数和零点能。实验结果表明，改进算法的复杂函数优化性能优于多种常见优化算法，对于Ackley、Griewank、Sphere、Sum Squares、Zakharov等高维标准测试函数均能以100%的概率获得全局最优解。

Abstract

An improved multi-scale quantum harmonic oscillator algorithm (MQHOA) with energy level stabilizing process was proposed analogizing to quantum harmonic oscillator's wave function. Inspired by quantum model

the op-timization problem was transformed to finding ground state wave function of bound state. Harmonic oscillator potential well was used to approach objective function under the condition of Taylor approximation. Energy level stabilization

en-ergy level reduction

scale reduction were the basic iterative convergence processes of MQHOA

coinciding with its physical model. Only one subjective control parameter was needed in MQHOA whose wave function and zero-point en-ergy were defined with reference to quantum model. Experimental results show that MQHOA's performance is superior to several other common optimization algorithms. For high dimensional testing functions including Ackley、Griewank、Sphere、Sum Squares、Zakharov

etc

the global optimums can be obtained precisely with 100% probability.

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references

BATTAGLIA D A , SANTORO G E , TOSATTI E . Optimization by quantum annealing: lessons from hard satisfiability problems [J ] . Physical Review E Statistical Nonlinear ＆ Soft Matter Physics , 2005 , 71 ( 6 ): 531 - 536 .

FINNILA A B , GOMEZ M A , SEBENIK C , et al . Quantum annealing:a new method for minimizing multidimensional functions [J ] . Chem Phys Lett , 1994 , 219 ( 5-6 ): 343 - 348 .

SOMMA R D , BOIXO S , BARNUM H , et al . Quantum simulations of classical annealing processes [J ] . Phys Rev Lett , 2008 , 101 ( 13 ): 130504 .

BROOKE J , BITKO D , ROSENBAUM T F , et al . Quantum annealing of a disordered spin system [J ] . Science , 2001 , 284 ( 5415 ): 779 - 781 .

SUN J , WU X J , VASILE P , et al . Convergence analysis and im-provements of quantum-behaved particle swarm optimization [J ] . In-formation Sciences , 2012 , 193 ( 15 ): 81 - 103 .

FENG B , SUN J , XU W B . A global search strategy of quan-tum-behaved particle swarm optimization [C ] // Proc of IEEE Confer-ence on Cybernetics and Intelligent Systems , c 2005 : 111 - 116 .

SUN J , FANG W , WU X J , et al . Quantum-behaved particle swarm optimization: analysis of the individual particle behavior and parame-ter selection [J ] . Evolutionary Computation , 2012 , 20 ( 3 ): 349 - 393 .

王鹏，黄焱，任超，等．多尺度量子谐振子高维函数全局优化算法 [J ] ．电子学报， 2013 , 41 ( 12 ): 2468 - 2473 .

WANG P , HUANG Y , REN C , et al . Multi-scale quantum harmonic oscillator for high-dimensional function global optimization algorithm [J ] . Acta Electronica Sinica , 2013 , 41 ( 12 ): 2468 - 2473 .

王鹏，黄焱．多尺度量子谐振子优化算法物理模型 [J ] ．计算机研究与探索， 2015 , 9 ( 10 ): 1271 - 1280 .

WANG P , HUANG Y . Multi-scale quantum harmonic oscillator for high-dimensional function global optimization algorithm [J ] . Acta Electronica Sinica , 2015 , 9 ( 10 ): 1271 - 1280 .

刘峰，王鹏，黄焱，等．多尺度量子谐振子优化算法实现方法研究 [J ] ．成都信息工程学院学报， 2015 , 30 ( 5 ): 433 - 438 .

LIU F , WANG P , HUANG Y , et al . Research on algorithm implementation of multi-scale quantum harmonic oscillator algorithm [J ] . Journal of Chengdu University of Information Technology , 2013 , 41 ( 12 ): 2468 - 2473 .

陆志军，安俊秀，王鹏．基于划分的多尺度量子谐振子算法多峰优化 [J ] ．自动化学报， 2016 , 42 ( 2 ): 235 - 245 .

LU Z J , AN J X , WANG P . Partition-based MQHOA for multimodal optimization [J ] . Acta Automatica Sinica , 2016 , 42 ( 2 ): 235 - 245 .

袁亚男，王鹏，刘峰．多尺度量子谐振子算法性能分析 [J ] ．计算机应用， 2015 , 35 ( 6 ): 1600 - 1604 .

YUN Y N , WANG P , LIU F . Performance analysis of multi-scale quantum harmonic oscillator algorithm [J ] . Journal of Computer Ap-plications , 2015 , 35 ( 6 ): 1600 - 1604 .

燕京京，王鹏，范家兵，等．基于量子谐振子模型的聚类中心选取算法 [J ] ．电子学报， 2016 , 44 ( 2 ): 405 - 412 .

YAN J J , WANG P , FAN J B , et al . Clustering center selecting algo-rithm based on quantum harmonic oscillator model [J ] . Acta Electronica Sinica , 2016 , 44 ( 2 ): 405 - 412 .

王鹏，黄焱，安俊秀，等．多尺度量子谐振子算法在组合优化问题中的性能分析 [J ] ．电子科技大学学报， 2016 , 45 ( 3 ): 469 - 474 .

WANG P , HUANG Y , AN J X , et al . MQHOA used in TSP problem [J ] . Journal of University of Electronic Science and Technology of China , 2016 , 45 ( 3 ): 469 - 474 .

黄焱，王鹏，谢高辉．基于PE方法的数据中心需量费用优化算法 [J ] . 通信学报， 2016 , 37 ( 3 ): 90 - 97 .

HUANG Y , WANG P , XIE G H . Optimizing demand charge of data center base on PE method [J ] . Journal on Communications , 2016 , 37 ( 3 ): 90 - 97 .

王鹏，黄焱，李坤，等．云计算集群相空间负载均衡度优先调度算法研究 [J ] ．计算机研究与发展， 2014 , 51 ( 5 ): 1095 - 1107 .

WANG P , HUANG Y , LI K , et al . Load balancing degree first algo-rithm on phase space for cloud computing cluster [J ] . Computer Research and Development , 2014 , 51 ( 5 ): 1095 - 1107 .

CHEN D B , ZOU F , LI Z , et al . An improved teaching–learning-based optimization algorithm for solving global optimization problem [J ] . Information Sciences , 297 ( 2015 ): 171 - 190 .

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