Multi-start jade with knowledge Transfer for numerical optimization

2009 IEEE Congress on Evolutionary Computation, CEC 2009

Volumn , Issue , 2009, Pages 1889-1895

  Peng, Fei ^a,b   Tang, Ke ^a,b   Chen, Guoliang ^a,b   Yao, Xin ^a,b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARK FUNCTIONS; CONTROL PARAMETERS; DIFFERENTIAL EVOLUTION; EXPERIMENTAL STUDIES; KNOWLEDGE TRANSFER; MULTISTART; NUMERICAL OPTIMIZATIONS; STOCHASTIC ALGORITHMS;

CONTROL SYSTEM ANALYSIS; EVOLUTIONARY ALGORITHMS; KNOWLEDGE MANAGEMENT;

SILICATE MINERALS;

EID: 70449989276     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2009.4983171     Document Type: Conference Paper

References (22)

1. R. Storn and K. Price, " Differential Evolution - a simple and efficient heuristic strategy for global optimization over continuous spaces, " Journal of Global Optimization, vol. 11, no. 4, pp. 341-359, Dec 1997.
2. K. Price, R. Storn, and J. Lampinen, Differential Evolution: A Practical Approach to Global Optimization. Springer-Verlag, ISBN: 3-540- 20950-6, 2005.
3. J. Zhang and A. Sanderson, " JADE: adaptive differential evolution with optional external archive, " Accepted by IEEE Transactions on Evolutionary Computation, May. 2008.
4. T. Bäck, " Evolutionary algorithms in theory and practice, " Oxford University Press, New York, 1996.
5. T. Bartz-Beielstein, Experimental Research in Evolutionary Computation: The New Experimentalism. Berlin Heidelberg: Springer-Verlag, 2006.
6. T. Bäck and H. Schwefel, " An overview of evolutionary algorithms for parameter optimization, " Evolutionary Computation, vol. 1, no. 1, pp. 1-23, 1993.
7. W. B. Langdon and R. Poli, " Evolving problems to learn about particle swarm optimizers and other search algorithms, " IEEE Transactions on Evolutionary Computation, vol. 11, no. 5, pp. 561-578, Oct. 2007.
8. N. Noman and H. Iba, " Accelerating Differential Evolution using an adaptive local search, " IEEE Transactions on Evolutionary Computation, vol. 12, no. 1, pp. 107-125, Feb. 2008.
9. Y. Shi and R. C. Eberhart, "A modified particle swarm optimizer, " in Proceedings of the 1998 IEEE Congress on Evolutionary Computation (CEC'98), pp. 69-73, Anchorage, AK, USA, 1998.
10. Z. Yang, K. Tang, and X. Yao, " Self-adaptive Differential Evolution with Neighborhood Search, " in Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC'08), pp. 1110-1116, Hongkong, 2008.
11. Z. Yang, K. Tang, and X. Yao, " Large scale evolutionary optimization using cooperative coevolution, " Information Sciences, vol. 178, no. 15, pp. 2985-2999, 2008.
12. J. J. Liang, A. K. Qin, P. N. Suganthan, and S. Baskar, " Comprehensive learning particle swarm optimizer for global optimization of multimodal functions, " IEEE Transactions on Evolutionary Computation, vol. 10, no. 3, pp. 281-295, Jun. 2006.
13. A. K. Qin and P. N. Suganthan, " Self-adaptive differential evolution algorithm for numerical optimization, " in Proceedings of the 2005 IEEE Congress on Evolutionary Computation (CEC'05), vol. 2, pp. 1785- 1791, Edinburgh, UK, 2005.
14. J. Brest, S. Greiner, B. Bošković, M. Mernik, and V. Žumer, " Selfadapting control parameters in differential evolution: a comparative study on numerical benchmark problems, " IEEE Transactions on Evolutionary Computation, vol. 10, no. 6, pp. 646-657, Dec. 2006.
15. Y. Wang and B. Li, " A restart univariate estimation of distribution algorithms: sampling under mixed Gaussian and Lévy probability distribution, " in Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC'08), pp. 3917-3924, Hongkong, 2008.
16. A. Auger and N. Hansen, " A restart CMA evolution strategy with increasing population size, " in Proceedings of the 2005 IEEE Congress on Evolutionary Computation (CEC'05), vol. 2, pp. 1769-1776, Edinburgh, UK, 2005.
17. F. Glover, " Heuristics for integer programming using surrogate constraints, " Decision Sciences, vol. 8, no. 1, pp. 156-166, 1977.
18. T. A. A. Victoire and A. E. Jeyakumar, " Unit commitment by a tabu-search-based hybrid-optimisation technique, " IEE Proceedings of Generation, Transmission and Distribution, vol. 152, no. 4, pp. 563- 574, 2005.
19. Y. Wang, Z. Zhao, and R. Ren, " Hybrid particle swarm optimizer with Tabu strategy for global numerical optimization, " in Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC'07), pp. 2310-2316, Singapore, 2007.
20. X. Yao, Y. Liu, and G. Lin, " Evolutionary programming made faster, " IEEE Transactions on Evolutionary Computation, vol. 3, no. 2, pp. 82- 102, Jul. 1999.
21. P. N. Suganthan, et. al, " Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization, " http://www.ntu.edu.sg/home/EPNSugan, 2005.
22. J. A. Vrugt, B. A. Robinson, and J. M. Hyman, " Self-adaptive multimethod search for global optimization in real-parameter spaces, " Accepted by IEEE Transactions on Evolutionary Computation, Feb. 2008.