Modified chaotic ant swarm to function optimization

doi:10.1016/S1005-8885(08)60179-X

中国邮电高校学报(英文) ›› 2009, Vol. 16 ›› Issue (1): 58-63.doi: 10.1016/S1005-8885(08)60179-X

• Artificial Intelligence • 上一篇下一篇

Modified chaotic ant swarm to function optimization

李玉英,温巧燕,李丽香

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-02-26
通讯作者: 李玉英

Modified chaotic ant swarm to function optimization

LI Yu-ying, WEN Qiao-yan, LI Li-xiang

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:1900-01-01 Revised:1900-01-01 Online:2009-02-26
Contact: LI Yu-ying

摘要/Abstract

摘要：

The chaotic ant swarm algorithm (CAS) is an optimization algorithm based on swarm intelligence theory, and it is inspired by the chaotic and self-organizing behavior of the ants in nature. Based on the analysis of the properties of the CAS, this article proposes a variation on the CAS called the modified chaotic ant swarm (MCAS), which employs two novel strategies to significantly improve the performance of the original algorithm. This is achieved by restricting the variables to search ranges and making the global best ant to learn from different ants’ best information in the end. The simulation of the MCAS on five benchmark functions shows that the MCAS improves the precision of the solution.

关键词:

chaotic;ant;swarm,;benchmark;functions,;modified;chaotic;ant;swarm,;swarm;intelligence

Abstract:

Key words:

chaotic ant swarm;benchmark functions;modified chaotic ant swarm;swarm intelligence

LI Yu-ying, WEN Qiao-yan, LI Li-xiang. Modified chaotic ant swarm to function optimization[J]. Acta Metallurgica Sinica(English letters), 2009, 16(1): 58-63.

参考文献

1. Bilchev G, Parmee I C. The ant colony metaphor for searching continuous design spaces. Lecture Notes in Computer Science, LNCS 993, Berlin, Germany: Springer-Verlag, 1995: 25-39

2. Mathur M, Karale S B, Priyee S, et al. Ant colony approach to continuous function optimization. Industral Engineering Chemistry Research, 2000, 39(10): 3814-3822

3. Dreo J, Siarry P. A new ant colony algorithm using the hierarchical concept aimed at optimization of multi-minima continuous functions. Lecture Notes in Computer Science, LNCS 2463, Berlin, Germany: Springer-Verlag, 2002: 216-221

4. Li L X, Peng H P, Wang X D, et al. An optimization method inspired by chaotic ant behavior. International Journal of Bifurcation and Chaos, 2006, 16(8): 2351-2364

5. Li Y Y, Li L X, Wen Q Y, et al. Data fitting via chaotic ant swarm. Proceedings of 2nd International Conference on Natural Computation, Sep 24-27 2006, Xi’an, China. Berlin, Germany: Springer-Verlag, 2006: 180-183

6. Li Y Y, Li L X, Wen Q Y, et al. Integer programming via chaotic ant swarm. The 3rd International Conference on Natural Computation: Vol 4, Aug 24-27 2007, Haikou, China. Berlin, Germany: Springer-Verlag, 2007: 489-493

7. Li L X, Yang Y X, Peng H P, et al. Parameters identification of chaotic systems via chaotic ant swarm. Chaos, Solitons and Fractals. 2006, 28(5): 1204-1211

8. Liang J J, Qin A K. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Transactions on Evolutionary Computation, 2006, 10(3): 281-295

9. Sole R V, Miramontes O, Goodwin B C. Oscillations and chaos in ant societies. Journal of Theoretical Biology, 1993, 161(3): 343-357

10. Tan Y, Deng C, He Z Y. A chaotic annealing neural network and its application to direction estimation of spatial signal sources. Proceedings of the 1997 IEEE Neural Networks for Signal Processing, Sep 24-26, 1997, Amelea, Island. Piscataway, NJ, USA: IEEE, 1997: 541-550

11. Ji M J, Tang H W. Application of chaos in simulated annealing. Chaos, Solitons and Fractals, 2004, 21(4): 933-941

12. Choi D. Cooperative mutation based evolutionary programming for continuous function optimization. Operations Research Letters, 2002, 30(3): 195-201

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Modified chaotic ant swarm to function optimization

Modified chaotic ant swarm to function optimization

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