Hybrid differential evolution for noisy optimization

2008 IEEE Congress on Evolutionary Computation, CEC 2008

Volumn , Issue , 2008, Pages 587-592

  Liu, Bo ^a   Zhang, Xuejun ^b   Ma, Hannan ^a  

^a TSINGHUA UNIVERSITY   (China)

^b BEIHANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ANNEALING; BENCHMARKING; BOOLEAN FUNCTIONS; BUDGET CONTROL; DIGITAL ARITHMETIC; EVOLUTIONARY ALGORITHMS; SIMULATED ANNEALING;

BENCHMARK PROBLEMS; DE ALGORITHMS; DIFFERENTIAL EVOLUTIONS; FUNCTION OPTIMIZATION PROBLEMS; HYBRID ALGORITHMS; HYBRID APPROACHES; HYBRID DIFFERENTIAL EVOLUTIONS; NEGATIVE INFLUENCES; NOISE MAGNITUDES; NOISY ENVIRONMENTS; NOISY OPTIMIZATIONS; OPTIMAL COMPUTING BUDGET ALLOCATIONS; OPTIMIZATION PROBLEMS; REAL APPLICATIONS; SEARCH MECHANISMS; SELECTION MECHANISMS; SIMULATED ANNEALING ALGORITHMS; UNCERTAIN ENVIRONMENTS;

OPTIMIZATION;

EID: 55849088752     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2008.4630855     Document Type: Conference Paper

References (17)

1. P.K. Bergey, C. Ragsdale, Modified differential evolution: a greedy random strategy for genetic recombination. Omega. 33: 255-265 (2005).
2. L. Bui, H. Abbass and D. Essam, "Fitness Inheritance for noisy evolutionary multi-objective optimization", Proceedings of the 2005 conference on Genetic and evolutionary computation: 779-785 (2005).
3. C.H. Chen, J. Lin, E. Yucesan, S.E. Chick, Simulation budget allocation for further enhancing the efficiency of ordinal optimization, Discret Event Dyn Syst 10 251-270. (2000)
4. J.P. Chiou, C.F. Chang, C.T. Su, Variable scaling hybrid differential evolution for solving network reconfiguration of distribution systems. IEEE Trans, Power Syst, 20: 668-674 (2005).
5. K. Dahal, G. Burt, G. McDonald and S. Galloway, GNSA-based hybrid techniques for the scheduling of generator maintenance in power systems, IEEE congress on Evolutionary Computation 1: 567-574 (2000).
6. S. Das and A. Konar, "Improved differential evolution algorithms for handling noisy optimization problems", IEEE congress on Evolutionary Computation: 1691-1698 (2005).
7. K. Deb, A. Pratap, S. Agarwal, et al., A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evolut. Comput. 6: 182-197 (2002).
8. H.Y. Fan, J. Lampinen, A trigonometric mutation operation to differential evolution. J. Global Optim. 27: 105-129 (2003).
9. V. Feoktistov, S. Janaqi, Generalization of the strategies in differential evolution. In: Proceedings of the 18th International Parallel and Distributed Processing Symposium, Santa Fe, New Mexico, 165-170 (2004).
10. Y. Jin, J. Branke, Evolutionary optimization in uncertain environments-A survey, IEEE Trans. Evolut. Comput. 9: 303-317 (2005).
11. P. Kaelo, M.M. Ali, A numerical study of some modified differential evolution algorithms. Eur. J. Oper. Res. 169: 1176-1184 (2006).
12. T. Krink, B. Filipic and G.B. Fogel, "Noisy optimization problems - a particular challenge for differential evolution?", IEEE congress on Evolutionary Computation: 332-339 (2004).
13. J. Lampinen, A Bibliography of Differential Evolution Algorithm. http://www.lut.fi/~jlampine/debiblio.htm, Oct 14, 2002.
14. B. Liu, L. Wang, Y.H. Jin, Advances in differential evolution. Control and Decision (in press).
15. R. Storn, Designing nonstandard filters with differential evolution, IEEE Signal Proc. Mag. 22: 103-106(2005),
16. R. Storn, K. Price, Differential Evolution - A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces. Technical Report TR-95-012, ICSI, http://http.icsi.berkeley.edu/~storn/litera.html, University of California, Berkeley, California, 2006,
17. L. Wang, Intelligent Optimization Algorithms with Applications. Tsinghua University & Springer Press, Beijing, 2001,