A bi-group differential artificial bee colony algorithm

Kongzhi Lilun Yu Yingyong/Control Theory and Applications

Volumn 28, Issue 2, 2011, Pages 266-272

  Bao, Li ^a,b   Zeng, Jian Chao ^a  

^a TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b Students' Affairs Department   (China)

Author keywords

Artificial bee colony; Bi group; Differential evolution; Opposition based learning

Indexed keywords

ARTIFICIAL BEE COLONIES; BENCHMARK FUNCTIONS; BI-GROUP; CONVERGENCE SPEED; DIFFERENTIAL EVOLUTION; DIFFERENTIAL EVOLUTION ALGORITHMS; INTELLIGENT BEHAVIOR; INTERACTIVE LEARNING; OPPOSITION-BASED LEARNING; OPTIMIZATION ABILITY; OPTIMIZATION STRATEGY; PREMATURE CONVERGENCE; SEARCH SPACES; STOCHASTIC OPTIMIZATION ALGORITHM; SUB-GROUPS;

EVOLUTIONARY ALGORITHMS; GLOBAL OPTIMIZATION; HEURISTIC ALGORITHMS; OPTIMIZATION;

CONVERGENCE OF NUMERICAL METHODS;

EID: 79955122463     PISSN: 10008152     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (20)

1. Karaboga D. An Idea Based on Honey Bee Swarm for Numerical Optimization[R]. Kayseri: Erciyes University, Engineering Faculty, Computer Engineering Department, 2005.
2. Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony(ABC) algorithm[J]. Journal of Global Optimization, 2007, 39(3): 459-471.
3. Karaboga D, Basturk B. On the performance of artificial bee colony(abc) algorithm[J]. Applied Soft Computing, 2008, 8(1): 687-697.
4. KARABOGA D, BASTURK B. Artificial bee colony(ABC) optimization algorithm for solving constrained optimization problems[C]//LNCS: Advances in Soft Computing: Foundations of Fuzzy Logic and Soft Computing. Berlin: Springer-Verlag, 2007, 4529: 789-798.
5. Karaboga D, Akay B B. Artificial bee colony algorithm on training artificial neural networks[C]//2007 IEEE 15th Signal Processing and Communications Applications Conference. New York: IEEE, 2007: 818-821.
6. Karaboga D, Akay B B, Ozturk C. Artificial bee colony(ABC) optimization algorithm for training feed-forward neural networks[C]//LNCS: Modeling Decisions for Artificial Intelligence. Berlin: Springer-Verlag, 2007, 4617: 318-319.
7. Karaboga N. A new design method based on artificial bee colony algorithm for digital IIR filters[J]. Journal of the Franklin Institute, 2009, 346(4): 328-348.
8. Srinivasa Rao R, Narasimham S V L, Ramalingaraju M. Optimization of distribution network configuration for loss reduction using artificial bee colony algorithm[J]. International Journal of Electrical Power and Energy Systems Engineering, 2008, 1(2): 709-715.
9. Hu Zhonghua, Zhao Min. Research on robot path planning based on ABC algorithm[J]. Electric Welding Machine, 2009, 39(4): 93-96.
10. Li Duanming, Cheng Bayi. Artificial bee colony algorithm for scheduling a single batch-processing machine with non-identical job sizes[J]. Journal of Sichuan University(Natural Science Edition), 2009, 46(3): 657-662.
11. SINGH A. An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem[J]. Applied Soft Computing, 2009, 9(2): 625-631.
12. Tsai P W, Pan J S, Liao B Y, et al. Enhanced artificial bee colony optimization[J]. International Journal of Innovative Computing, Information and Control, 2009, 5(12): 5081-5092.
13. Ding Haijun, Li Fenglei. Bee colony algorithm for TSP problem and parameter improvement[J]. China Science and Technology Information, 2008, (3): 241-243.
14. Kang Fei. Improved artificial bee colony algorithm and its application in back analysis[J]. Water Resources and Power, 2009, 27(1): 126-129.
15. Storn R, Price K. Differential evolution-a simple and efficient heuristic for global optimization over continuous space[J]. Journal of Global Optimization, 1997, 11(4): 341-359.
16. Mendes R, Mohais A S. DynDE: a differential evolution for dynamic optimization problems[C]//2005 IEEE Congress on Evolutionary Computation. New York: IEEE, 2005: 2808-2815.
17. Wu Yu, Li Yuanxiang, Xu Xing. Novel oppositional hybrid differential evolution algorithm based on swarm intelligence[J]. Journal of Chinese Computer Systems, 2009, 5(4): 903-907.
18. Bao L, Zeng J C. Comparison and analysis of the selection mechanism in the artificial bee colony algorithm[C]//2009 9th International Conference on Hybrid Intelligent Systems. Los Alamitos, CA: IEEE Computer Society, 2009: 411-416.
19. Mao Runyu, Wang Xiaoping, Xue Xiaoping. An adaptive differential evolution algorithm[J]. Computer Applications and Software, 2008, 25(12): 7-8.
20. Yao X, Liu Y, Lin G M. Evolutionary programming made faster[J]. IEEE Transactions on Evolutionary Computation, 1999, 3(2): 82-102.