MQHOA优化算法能级稳定过程及判据研究
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摘要
多尺度量子谐振子算法(MQHOA)的能级稳定过程是算法的核心部分,对于避免算法陷入局部最优、提高算法求解精度具有重要作用.对算法能级稳定过程进行研究,发现不同的能级稳定判据,会造成算法在同一能级下不同的表现.相对宽松的判据使算法在能级稳定过程中迭代不充分,容易陷入早熟.而更严格的判据能使波函数在同一能级下达到稳定状态,提高算法的全局搜索能力,但会增加算法的计算代价.通过实验证明,相对宽松的能级稳定判据对单峰简单函数具有良好的求解效果,严格的能级稳定判据适用于算法对多峰复杂函数的求解.算法在资源优化、自适应控制及能耗优化管理等方面已取得有效应用.
The energy level stabilization process of the multi-scale quantum harmonic oscillator algorithm(MQHOA) is the core part of the algorithm,which plays an important role in avoiding the algorithm falling into local optimum and improving the accuracy of the algorithm.In the studying of the energy level stabilization process of the algorithm,it is found that different energy level stabilization criteria will result in different performance of the algorithm at the same energy level.The relatively loose criterion makes the iteration of the algorithm inadequate in the process of energy level stabilization and easy to fall into premature.The more stringent criterion can make the wave function reach a stable state at the same energy level,improve the global search ability of the algorithm,but meanwhile the computing cost will also rise.Experiments show that loose energy level stability criterion of the algorithm has good effect on solving unimodal simple functions,and strict energy level stability criterion of it is suitable for solving multimodal complex functions.The algorithm has been effectively applied in resource optimization,adaptive control and energy consumption optimization management.
The energy level stabilization process of the multi-scale quantum harmonic oscillator algorithm(MQHOA) is the core part of the algorithm,which plays an important role in avoiding the algorithm falling into local optimum and improving the accuracy of the algorithm.In the studying of the energy level stabilization process of the algorithm,it is found that different energy level stabilization criteria will result in different performance of the algorithm at the same energy level.The relatively loose criterion makes the iteration of the algorithm inadequate in the process of energy level stabilization and easy to fall into premature.The more stringent criterion can make the wave function reach a stable state at the same energy level,improve the global search ability of the algorithm,but meanwhile the computing cost will also rise.Experiments show that loose energy level stability criterion of the algorithm has good effect on solving unimodal simple functions,and strict energy level stability criterion of it is suitable for solving multimodal complex functions.The algorithm has been effectively applied in resource optimization,adaptive control and energy consumption optimization management.
引文
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[15] 邓怀勇,马琴,陈国彬,等.基于量子谐振子的RoQ攻击识别方法[J].四川大学学报(自然科学版),2018,55(4):752-756.DENG H Y,MA Q,CHEN G B,et al.The RoQ attack recognition method based on quantum harmonic oscillator[J].Journal of Sichuan University (Natural Science Edition),2018,55(4):752-756.(in Chinese)
[16] 李磊,马宪民,范文玲.一种矿用电缆剩余寿命预测方法[J].工矿自动化,2018,44(8):57-62.LI L,MA X M,FAN W L.A residual life prediction method of mine-used cable[J].Industry and Mine Automation,2018,44(8):57-62.(in Chinese)
[17] 王鹏,黄焱.具有能级稳定过程的MQHOA优化算法[J].通信学报,2016,37(7):79-86.WANG P,HUANG Y.MQHOA algorithm with energy level stabilizing process[J].Journal on Communications,2016,37(7):79-86.(in Chinese)
[18] WANG P,LI B,JIN J,et al.Multi-scale quantum harmonic oscillator algorithm with Individual stabilization strategy[A] International Conference on Swarm Intelligence[C].Cham:Springer,2018.624-633.
[2] Brooke J,Bitko D,Rosenbaum T F,et al.Quantumannealing of a disordered spin system[J].Science,2001,284(5415):779-781.
[3] 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.(in Chinese)
[4] SUN J,XU W,FENG B.A global search strategy of quantum-behaved particle swarm optimization[A] Proc IEEE Conference on Cybernetics and Intelligent Systems[C].Singapore:IEEE,2004.111-116.
[5] SUNAA J,FANG W,LAI C H,et al.Convergence analysis and improvements of quantum-behaved particle swarm optimization[J].Information Sciences,2012,193(15):81-103.
[6] SUN J,FANG W,WU X,et al.Quantum-behaved particle swarm optimization:analysis of individual particle behavior and parameter selection[J].Evolutionary Computation,2012,20(3):349-393.
[7] WANG P,YE X G,LI B,et al.Multi-scale quantum harmonic oscillator algorithm for global numerical optimization[J].Applied Soft Computing,2018,69(C):655-670.
[8] 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 onalgorithm implementation of multi-scale quantum harmonic oscillator algorithm[J].Journal of Chengdu University of Information Technology,2015,30(5):433-438.(in Chinese)
[9] 王鹏,黄焱.多尺度量子谐振子优化算法物理模型[J].计算机科学与探索,2015,9(10):1271-1280.WANG P,HUANG Y.Physical model of multi-scale quantum harmonic oscillator optimization algorithm[J].Journal of Frontiers of Computer Science & Technology,2015,9(10):1271-1280.(in Chinese)
[10] 王鹏,黄焱,袁亚男,等.多尺度量子谐振子算法的收敛特性[J].电子学报,2016,44(8):1988-1993.WANG P,HUANG Y,YUAN Y N,et al.Convergence characteristics of multi-scale quantum harmonic oscillator algorithm[J].Acta Electronica Sinica,2016,44(8):1988-1993.(in Chinese)
[11] WANG P,CHENG K,HUANG Y,et al.Multiscale quantum harmonic oscillator algorithm for multimodal optimization[J].Computational Intelligence and Neuroscience,2018,2018(95001):1-12.
[12] 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.YUAN Y N,WANG P,LIU F.Performance analysis of multi-scale quantum harmonic oscillator algorithm[J].Journal of Computer Applications,2015,35(6):1600-1604.(in Chinese)
[13] 胡思杰,徐松涛,史忠亚,等.基于IFS-IMQHOA算法的干扰资源分配决策优化[J].计算机工程与应用,2017,53(19):252-256.HU S J,XU S T,SHI Z Y,XIN P,et al.Optimization of jamming resources distribution decision based on IFS-IMQHOA algorithm[J].CEA,2017,53(19):252-256.(in Chinese)
[14] 史忠亚,吴华,沈文迪,等.考虑射频隐身的雷达功率自适应管控方法[J].现代雷达,2017,39(10):6-10.SHIZ Y,WU H,SHEN W D,et al.A method of radar power self-adapting control considering radio frequency stealth[J].Modern Radar,2017,39(10):6-10.(in Chinese)
[15] 邓怀勇,马琴,陈国彬,等.基于量子谐振子的RoQ攻击识别方法[J].四川大学学报(自然科学版),2018,55(4):752-756.DENG H Y,MA Q,CHEN G B,et al.The RoQ attack recognition method based on quantum harmonic oscillator[J].Journal of Sichuan University (Natural Science Edition),2018,55(4):752-756.(in Chinese)
[16] 李磊,马宪民,范文玲.一种矿用电缆剩余寿命预测方法[J].工矿自动化,2018,44(8):57-62.LI L,MA X M,FAN W L.A residual life prediction method of mine-used cable[J].Industry and Mine Automation,2018,44(8):57-62.(in Chinese)
[17] 王鹏,黄焱.具有能级稳定过程的MQHOA优化算法[J].通信学报,2016,37(7):79-86.WANG P,HUANG Y.MQHOA algorithm with energy level stabilizing process[J].Journal on Communications,2016,37(7):79-86.(in Chinese)
[18] WANG P,LI B,JIN J,et al.Multi-scale quantum harmonic oscillator algorithm with Individual stabilization strategy[A] International Conference on Swarm Intelligence[C].Cham:Springer,2018.624-633.
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