A novel Two-layer Hierarchical Differential Evolution Algorithm for Global Optimization

被引：3
作者：
Zhou, Yinzhi [1 ]
Li, Xinyu [1 ]
Gao, Liang [1 ]
机构：
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013) | 2013年
关键词：
differential evolution; two-layer hierarchy; global optimization; PARAMETERS;
D O I：
10.1109/SMC.2013.497
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a novel Two-layer Hierarchical differential evolution (THDE) algorithm to improve the search ability of differential evolution (DE) algorithm. Individuals are separated into bottom layer and top layer. In the bottom layer, individuals are divided into several groups. Modified DE/current-best/1/bin strategy is conducted to produce offspring, where the best individual comes from top layer. In the top layer, modified DE/rand/1/bin strategy is used to update individuals. A set of famous benchmark functions has been used to test and evaluate the performance of the proposed THDE. The experimental results show that the proposed algorithm is better than DE/current-best/1/bin and DE/rand/1/bin and better than or at least comparable to the self-adaptive DE (JDE) and intersect mutation differential evolution algorithm (IMDE) for most functions.
引用
收藏
页码：2916 / 2921
页数：6
相关论文
共 14 条
[1]  
[Anonymous], 2002, ADV INTELL SYST FUZZ
[2]   Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems [J].
Brest, Janez ;
Greiner, Saso ;
Boskovic, Borko ;
Mernik, Marjan ;
Zumer, Vijern .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2006, 10 (06) :646-657
[3]   Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators [J].
Epitropakis, Michael G. ;
Tasoulis, Dimitris K. ;
Pavlidis, Nicos G. ;
Plagianakos, Vassilis P. ;
Vrahatis, Michael N. .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2011, 15 (01) :99-119
[4]   A numerical study of some modified differential evolution algorithms [J].
Kaelo, P ;
Ali, MM .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 169 (03) :1176-1184
[5]   Differential evolution algorithm with ensemble of parameters and mutation strategies [J].
Mallipeddi, R. ;
Suganthan, P. N. ;
Pan, Q. K. ;
Tasgetiren, M. F. .
APPLIED SOFT COMPUTING, 2011, 11 (02) :1679-1696
[6]   Bare bones differential evolution [J].
Omran, Mahamed G. H. ;
Engelbrecht, Andries P. ;
Salman, Ayed .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2009, 196 (01) :128-139
[7]   Parent-centric differential evolution algorithm for global optimization problems [J].
Pant M. ;
Ali M. ;
Singh V.P. .
OPSEARCH, 2009, 46 (2) :153-168
[8]   Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization [J].
Qin, A. K. ;
Huang, V. L. ;
Suganthan, P. N. .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2009, 13 (02) :398-417
[9]  
Ronkkonen J., 2005, IEEE CEC 2005, V1, P567
[10]   Differential evolution - A simple and efficient heuristic for global optimization over continuous spaces [J].
Storn, R ;
Price, K .
JOURNAL OF GLOBAL OPTIMIZATION, 1997, 11 (04) :341-359
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