基于圆形信赖域的改进和声搜索算法

doi:10.11772/j.issn.1001-9081.2015.04.1049

计算机应用 ›› 2015, Vol. 35 ›› Issue (4): 1049-1056.DOI: 10.11772/j.issn.1001-9081.2015.04.1049

基于圆形信赖域的改进和声搜索算法

刘乐

济南大学管理学院, 济南 250002

收稿日期:2014-11-09 修回日期:2015-01-01 出版日期:2015-04-10 发布日期:2015-04-08
通讯作者: 刘乐
作者简介:刘乐 (1984-),男,山东济南人,讲师,博士,主要研究方向:智能优化算法、生产调度与重调度。
基金资助:
国家自然科学基金资助项目(71071008);教育部人文社会科学研究青年基金资助项目(14YJCZH098);济南大学科研基金资助项目(XKY1322)。

Improved harmony search algorithm based on circular trust region

LIU Le

School of Management, University of Jinan, Jinan Shandong 250002, China

Received:2014-11-09 Revised:2015-01-01 Online:2015-04-10 Published:2015-04-08

摘要/Abstract

摘要：

针对标准和声搜索(HS)算法易陷入局部最优、收敛精度不高的不足,提出了一种基于圆形信赖域(CTR)的新型和声搜索算法——CTRHS。该算法运用逐双音调一次性产生方式,在记忆思考环节交互式地采取面向圆形信赖域的集约化思考操作,在双音调微调环节利用当前和声记忆库中的最好或最差和声来确定微调带宽,并且以新生成和声直接替换当前和声记忆库中最差和声来实现和声记忆库的更新。通过在9种标准测试函数上对CTRHS算法进行实验验证和算法性能对比,结果表明CTRHS算法在解质量、收敛性能上优于文献中已报道的7种HS改进算法,且当和声记忆库规模(HMS)、和声记忆库思考率(HMCR)分别取5和0.99时,它能表现出更佳的全局优化性能。

关键词: 和声搜索, 和声记忆库, 记忆思考, 音调微调, 信赖域

Abstract:

Concerning the drawbacks of trapping in local optimal solutions and low convergence accuracy of standard Harmony Search (HS) algorithm, a new harmony search algorithm based on Circular Trust Region (CTR), named as CTRHS, was proposed. CTRHS adopted the one-off generation mode of two pitches. Intensive considerations within the circular trust region were interactively conducted in its memory considering process. Adjustment bandwidth was determined by means of the best or worst harmony vector of current Harmony Memory (HM) during the adjusting process of double pitches. The update of HM was achieved by replacing the worst harmony in current HM with the newly generated harmony. Computational experiments were conducted upon 9 benchmark functions to validate the performance of CTRHS. As demonstrated in the results, CTRHS outperforms other 7 reported HS variants in terms of solution quality and convergence efficiency. Moreover, when the parameters of Harmony Memory Size (HMS) and Harmony Memory Considering Rate (HMCR) are respectively equal to 5 and 0.99, it has better performance in searching the global optimal solutions.

Key words: Harmony Search (HS), harmony memory, memory consideration, pitch adjustment, trust region

中图分类号:

TP301.6

刘乐. 基于圆形信赖域的改进和声搜索算法[J]. 计算机应用, 2015, 35(4): 1049-1056.

LIU Le. Improved harmony search algorithm based on circular trust region[J]. Journal of Computer Applications, 2015, 35(4): 1049-1056.

参考文献

[1] GEEM Z W, KIM J H, LOGANATHAN G V. A new heuristic optimization algorithm: harmony search [J]. Simulation, 2001, 76(2): 60-68.
[2] ZOU D, GAO L, WU J, et al. A novel global harmony search algorithm for reliability problems [J]. Computers and Industrial Engineering, 2010, 58(2): 307-316.
[3] FOURIE J, MILLS S, GREEN R. Harmony filter: a robust visual tracking system using the improved harmony search algorithm [J]. Image and Vision Computing, 2010, 28(12): 1702-1716.
[4] MURREN P, KHANDELWAL K. Design-Driven Harmony Search (DDHS) in steel frame optimization [J]. Engineering Structures, 2014, 59: 798-808.
[5] DIAO R, SHEN Q. Feature selection with harmony search [J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2012, 42(6): 1509-1523.
[6] ASKARZADEH A, ZEBARJADI M. Wind power modeling using harmony search with a novel parameter setting approach [J]. Journal of Wind Engineering and Industrial Aerodynamics, 2014, 135: 70-75.
[7] LAYEB A. A hybrid quantum inspired harmony search algorithm for 0-1 optimization problems [J]. Journal of Computational and Applied Mathematics, 2013, 253: 14-25.
[8] ZOU D, GAO L, LI S, et al. A novel global harmony search algorithm for task assignment problem [J]. Journal of Systems and Software, 2010, 83(10): 1678-1688.
[9] MOHAMMED H, MASRI A, NASSER R S, et al. A harmony search algorithm for nurse rostering problems [J]. Information Sciences, 2013, 233: 126-140.
[10] YUAN Y, XU H, YANG J. A hybrid harmony search algorithm for the flexible job shop scheduling problem [J]. Applied Soft Computing, 2013, 13(7): 3259-3272.
[11] 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.
[12] WANG C, HUANG Y. Self-adaptive harmony search algorithm for optimization [J]. Expert Systems with Applications, 2010, 37(4): 2826-2837.
[13] ENAYATIFAR R, YOUSEFI M, ABDULLAH A H, et al. LAHS: a novel harmony search algorithm based on learning automata [J]. Communications in Nonlinear Science and Numerical Simulation, 2013, 18(12): 3481-3497.
[14] OMRAN M G H, MAHDAVI M. Global-best harmony search [J]. Applied Mathematics and Computation, 2008, 198(2): 643-656.
[15] PAN Q K, SUGANTHAN P N, TASGETIREN M F, et al. A self-adaptive global best harmony search algorithm for continuous optimization problems [J]. Applied Mathematics and Computation, 2010, 216(3): 830-848.
[16] ZOU D, GAO L, WU J, et al. Novel global harmony search algorithm for unconstrained problems [J]. Neurocomputing, 2010, 73(16/17/18): 3308-3318.
[17] CHEN J, PAN Q, LI J. Harmony search algorithm with dynamic control parameters [J]. Applied Mathematics and Computation, 2012, 219(2): 592-604.
[18] YADAV P, RAJESH K, PANDA S K, et al. An intelligent tuned harmony search algorithm for optimization [J]. Information Sciences, 2012, 196: 47-72.
[19] EL-ABD M. An improved global-best harmony search algorithm [J]. Applied Mathematics and Computation, 2013, 222: 94-106.
[20] KHALILI M, KHARRAT R, SALAHSHOOR K, et al. Global dynamic harmony search algorithm: GDHS [J]. Applied Mathematics and Computation, 2014, 228: 195-219.
[21] CHAKRABORTY P, ROY G G, DAS S, et al. An improved harmony search algorithm with differential mutation operator [J]. Fundamenta Informticae, 2009, 95(4): 401-426.
[22] WU B, QIAN C, NI W, et al. Hybrid harmony search and artificial bee colony algorithm for global optimization problems [J]. Computers and Mathematics with Applications, 2012, 64(8): 2621-2634.
[23] KULLUK S. A novel hybrid algorithm combining hunting search with harmony search algorithm for training neural networks [J]. Journal of the Operational Research Society, 2013, 64(5): 748-761.
[24] TANG K, LI X, SUGANTHAN P N, et al. Benchmark functions for the CEC 2010 special session and competition on large-scale global optimization [EB/OL].[2013-12-01]. http://sci2s.ugr.es/eamhco/cec2010_functions.pdf.

基于圆形信赖域的改进和声搜索算法

Improved harmony search algorithm based on circular trust region

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