[1]黎延海,拓守恒.一种求解多模态复杂问题的混合和声差分算法[J].智能系统学报,2018,13(2):281-289.[doi:10.11992/tis.201612030]
 LI Yanhai,TUO Shouheng.Hybrid algorithm based on harmony search and differential evolution for solving multi-modal complex problems[J].CAAI Transactions on Intelligent Systems,2018,13(2):281-289.[doi:10.11992/tis.201612030]
点击复制

一种求解多模态复杂问题的混合和声差分算法

参考文献/References:
[1] TRELEA I C. The particle swarm optimization algorithm: convergence analysis and parameter selection[J]. Information processing letters, 2003, 85(6): 317-325.
[2] DAS S, SUGANTHAN P N. Differential evolution: a survey of the state-of-the-art[J]. IEEE transactions on evolutionary computation, 2011, 15(1): 4-31.
[3] DASGUPTA K, MANDAL B, DUTTA P, et al. A genetic algorithm (GA) based load balancing strategy for cloud computing[J]. Procedia technology, 2013, 10: 340-347.
[4] DEEPA O, SENTHILKUMAR A. Swarm intelligence from natural to artificial systems: ant colony optimization[J]. International journal on applications of graph theory in wireless Ad hoc networks and sensor networks, 2016, 8(1): 9-17.
[5] MAHDAVI M, FESANGHARY M, DAMANGIR E. An improved harmony search algorithm for solving optimization problems[J]. Applied mathematics and computation, 2007, 188(2): 1567-1579.
[6] ZOU Dexuan, GAO Liqun, WU Jianhua, et al. Novel global harmony search algorithm for unconstrained problems[J]. Neurocomputing, 2010, 73(16/17/18): 3308-3318.
[7] 夏红刚, 欧阳海滨, 高立群. 多子群混合和声搜索算法[J]. 东北大学学报: 自然科学版, 2015, 36(2): 171-175, 187.
XIA Honggang, OUYANG Haibin, GAO Liqun. Multiple-sub-groups hybrid harmony search algorithm[J]. Journal of Northeastern university: natural science, 2015, 36(2): 171-175, 187.
[8] 拓守恒, 雍龙泉, 邓方安. 动态调整策略改进的和声搜索算法[J]. 智能系统学报, 2015, 10(2): 307-315.
TUO Shouheng, YONG Longquan, DENG Fang’an. Dynamic adjustment strategy for improving the harmony search algorithm[J]. CAAI transactions on intelligent systems, 2015, 10(2): 307-315.
[9] 夏红刚, 欧阳海滨, 高立群, 等. 全局竞争和声搜索算法[J]. 控制与决策, 2016, 31(2): 310-316.
XIA Honggang, OUYANG Haibin, GAO Liqun, et al. Global competitive harmony search algorithm[J]. Control and decision, 2016, 31(2): 310-316.
[10] WANG Yong, CAI Zixing, ZHANG Qingfu. Differential evolution with composite trial vector generation strategies and control parameters[J]. IEEE transactions on evolutionary computation, 2011, 15(1): 55-66.
[11] QIN A K, HUANG V L, SUGANTHAN P N. Differential evolution algorithm with strategy adaptation for global numerical optimization[J]. IEEE transactions on evolutionary computation, 2009, 13(2): 398-417.
[12] 李荣雨, 陈庆倩, 陈菲尔. 改进种群多样性的双变异差分进化算法[J]. 运筹学学报, 2017, 21(1): 44-54.
LI Rongyu, CHEN Qingqian, CHEN Feier. Differential evolution algorithm with double mutation strategies for improving population diversity[J]. Operations research transactions, 2017, 21(1): 44-54.
[13] WANG Ling, LI Lingpo. A coevolutionary differential evolution with harmony search for reliability-redundancy optimization[J]. Expert systems with applications, 2012, 39(5): 5271-5278.
[14] ARUL R, RAVI G, VELUSAMI S. Chaotic self-adaptive differential harmony search algorithm based dynamic economic dispatch[J]. International journal of electrical power and energy systems, 2013, 50: 85-96.
[15] 雍龙泉, 刘三阳, 张建科, 等. 基于差分算子的和声搜索算法求解非线性l1模极小化问题[J]. 兰州大学学报: 自然科学版, 2013, 49(4): 541-546.
YONG Longquan, LIU Sanyang, ZHANG Jianke, et al. Improved harmony search algorithm with differential operator for nonlinear l1 norm minimization problems[J]. Journal of Lanzhou university: natural sciences, 2013, 49(4): 541-546.
[16] YONG Longquan, LIU Sanyang. An improved harmony search algorithm with differential operator for absolute value equation[J]. ICIC express letters, 2014, 8(4): 1151-1157.
[17] ABEDINPOURSHOTORBAN H, HASAN S, SHAMSUDDIN S M, et al. A differential-based harmony search algorithm for the optimization of continuous problems[J]. Expert systems with applications, 2016, 62: 317-332.
[18] TANG K, YAO X, SUGANTHAN P N, et al. Benchmark functions for the CEC’2008 special session and competition on large scale global optimization[R]. Technical Report. China: Nature Inspired Computation and Applications Laboratory, USTC, 2007.
[19] TANG Ke, LI Xiaohong, SUGANTHAN P N, et al. Benchmark functions for the CEC’2010 special session and competition on large-scale global optimization[R]. Technical Report. Nanyang: Nature Inspired Computation and Applications Laboratory, USTC, China and Nanyang Technological University, 2009.
相似文献/References:
[1]刘三阳,张晓伟.混合差分变异策略[J].智能系统学报,2008,3(6):487.
 LIU San-yang,ZHANG Xiao-wei.A hybrid strategy for differential variation[J].CAAI Transactions on Intelligent Systems,2008,3():487.
[2]杨振宇,唐珂.差分进化算法参数控制与适应策略综述[J].智能系统学报,2011,6(5):415.
 YANG Zhenyu,TANG Ke.An overview of parameter control and adaptation strategiesin differential evolution algorithm[J].CAAI Transactions on Intelligent Systems,2011,6():415.
[3]毕晓君,刘国安,肖婧.基于自适应差分进化的干线交通信号协调控制[J].智能系统学报,2012,7(5):437.
 BI Xiaojun,LIU Guoan,XIAO Jing.Coordination and control of arterial traffic signalsbased on adaptive differential evolution[J].CAAI Transactions on Intelligent Systems,2012,7():437.
[4]杨艳霞.一种基于模拟退火操作的混合差分进化算法[J].智能系统学报,2014,9(1):109.[doi:10.3969/j.issn.1673-4785.201305027]
 YANG Yanxia.A hybrid differential evolutionary algorithm based on the simulated annealing operation[J].CAAI Transactions on Intelligent Systems,2014,9():109.[doi:10.3969/j.issn.1673-4785.201305027]
[5]丁青锋,尹晓宇.差分进化算法综述[J].智能系统学报,2017,12(4):431.[doi:10.11992/tis.201605015]
 DING Qingfeng,YIN Xiaoyu.Research survey of differential evolution algorithms[J].CAAI Transactions on Intelligent Systems,2017,12():431.[doi:10.11992/tis.201605015]
[6]谭旭杰,邓长寿,吴志健,等.云环境下求解大规模优化问题的协同差分进化算法[J].智能系统学报,2018,13(2):243.[doi:10.11992/tis.201706053]
 TAN Xujie,DENG Changshou,WU Zhijian,et al.Cooperative differential evolution in cloud computing for solving large-scale optimization problems[J].CAAI Transactions on Intelligent Systems,2018,13():243.[doi:10.11992/tis.201706053]
[7]林锦,胡家琛,刘莞玲,等.利用MISA多目标优化的置信规则库分类算法[J].智能系统学报,2019,14(5):982.[doi:10.11992/tis.201809022]
 LIN Jin,HU Jiachen,LIU Wanling,et al.Belief rule base classification algorithm using MISA multi-objective optimization[J].CAAI Transactions on Intelligent Systems,2019,14():982.[doi:10.11992/tis.201809022]
[8]吴莹莹,丁肇红,刘华平,等.面向环境探测的多智能体自组织目标搜索算法[J].智能系统学报,2020,15(2):289.[doi:10.11992/tis.201908023]
 WU Yingying,DING Zhaohong,LIU Huaping,et al.Self-organizing target search algorithm of multi-agent system for envi-ronment detection[J].CAAI Transactions on Intelligent Systems,2020,15():289.[doi:10.11992/tis.201908023]
[9]项前,周亚云,陆枳屹,等.响应动态约束条件的多目标货位优化算法研究[J].智能系统学报,2020,15(5):925.[doi:10.11992/tis.201906041]
 XIANG Qian,ZHOU Yayun,LU Zhiyi,et al.Multi-objective location optimization algorithm in response to dynamic constraints[J].CAAI Transactions on Intelligent Systems,2020,15():925.[doi:10.11992/tis.201906041]

备注/Memo

收稿日期:2016-12-26。
基金项目:国家自然科学基金项目(11401357);陕西省教育厅科研项目(14JK1130);陕西理工大学校级科研项目(SLGKY2017-05).
作者简介:黎延海,男,1981年生,讲师,硕士,主要研究方向为智能优化算法及应用;拓守恒,男,1978年生,副教授,博士研究生,CCF会员,主要研究方向为智能优化算法、生物信息分析与处理,发表学术论文多篇。
通讯作者:黎延海.E-mail:Chenxi81991@sina.com.

更新日期/Last Update: 1900-01-01
Copyright @ 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134