Journal of Global Optimization

, Volume 11, Issue 4, pp 341–359 | Cite as

Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces

  • Rainer Storn
  • Kenneth Price


A new heuristic approach for minimizing possiblynonlinear and non-differentiable continuous spacefunctions is presented. By means of an extensivetestbed it is demonstrated that the new methodconverges faster and with more certainty than manyother acclaimed global optimization methods. The newmethod requires few control variables, is robust, easyto use, and lends itself very well to parallelcomputation.

Stochastic optimization nonlinear optimization global optimization genetic algorithm evolution strategy 


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  1. 1.
    Aluffi-Pentini, F., Parisi, V. and Zirilli, F. (1985), Global Optimization and Stochastic Differential Equations, Journal of Optimization Theory and Applications47(1), 1–16.Google Scholar
  2. 2.
    Brayton, H., Hachtel, G. and Sangiovanni-Vincentelli, A. (1981), A Survey of Optimization Techniques for Integrated Circuit Design, Proceedings of the IEEE69, pp. 1334–1362.Google Scholar
  3. 3.
    Bunday, B.D. and Garside G.R. (1987), Optimisation Methods in Pascal, Edward Arnold Publishers.Google Scholar
  4. 4.
    Corana, A., Marchesi, M., Martini, C. and Ridella, S. (1987), Minimizing Multimodal Functions of Continuous Variables with the “Simulated Annealing Algorithm”, ACM Transactions on Mathematical Software, March 1987, pp. 272–280.Google Scholar
  5. 5.
    Goldberg, D.E. (1989), Genetic Algorithms in Search, Optimization & Machine Learning, Addison-Wesley.Google Scholar
  6. 6.
    Griewangk, A.O. (1981), Generalized Descent for Global Optimization, JOTA34, 11–39.Google Scholar
  7. 7.
    Ingber, L. and Rosen, B. (1992), Genetic Algorithms and Very Fast Simulated Reannealing: A Comparison, J. of Mathematical and Computer Modeling16(11), 87–100.Google Scholar
  8. 8.
    Ingber, L. (1993), Simulated Annealing: Practice Versus Theory, J. of Mathematical and Computer Modeling18(11), 29–57.Google Scholar
  9. 9.
    Lueder, E. (1990), Optimization of Circuits with a Large Number of Parameters, Archiv fuer Elektronik und Uebertragungstechnik44(2), 131–138.Google Scholar
  10. 10.
    Muehlenbein, H. and Schlierkamp-Vosen (1993), Predictive Models for the Breeder Genetic Algorithm, I. Continuous Parameter Optimizations, Evolutionary Computation1(1), 25–49.Google Scholar
  11. 11.
    Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P. (1992), Numerical Recipes in C, Cambridge University Press.Google Scholar
  12. 12.
    Price, K. (1994), Genetic Annealing, Dr. Dobb’s Journal, Oct. 1994, 127–132.Google Scholar
  13. 13.
    Price, K. and Storn, R. (1996), Minimizing the Real Functions of the ICEC’96 contest by Differential Evolution, IEEE International Conference on Evolutionary Computation(ICEC’96), may 1996, pp. 842–844.Google Scholar
  14. 14.
    Price, K. (1996), Differential Evolution: A Fast and Simple Numerical Optimizer, NAFIPS’96, pp. 524–527.Google Scholar
  15. 15.
    Rabiner, L.R. and Gold, B. (1975), Theory and Applications of Digital Signal Processing, Prentice-Hall, Englewood Cliffs, N.J..Google Scholar
  16. 16.
    Rechenberg, I. (1973), Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Frommann-Holzboog, Stuttgart.Google Scholar
  17. 17.
    Schwefel, H.P. (1995), Evolution and Optimum Seeking, John Wiley.Google Scholar
  18. 18.
    Storn, R. (1995), Constrained Optimization, Dr. Dobb’s Journal, May 1995, 119–123.Google Scholar
  19. 19.
    Storn, R. (1996a), Differential Evolution Design of an IIR-Filter, IEEE International Conference on Evolutionary Computation(ICEC’96), May 1996, pp. 268–273.Google Scholar
  20. 20.
    Storn, R. (1996b), On the Usage of Differential Evolution for Function Optimization, NAFIPS’96, pp. 519–523.Google Scholar
  21. 21.
    Storn, R. (1996c), Design of an FIR-filter with Differential Evolution, private communication, 1996.Google Scholar
  22. 22.
    Voigt, H.-M. (1995), Soft Genetic Operators in Evolutionary Computation, Evolution and Biocomputation, Lecture Notes in Computer Science 899, Springer, Berlin, pp. 123–141.Google Scholar
  23. 23.
    Zimmermann, W. (1990), Operations Research, Oldenbourg.Google Scholar
  24. 24.
    Ziny, F., Optimization of routing control with Differential Evolution, private communication, 1995.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Rainer Storn
    • 1
  • Kenneth Price
    • 2
  1. 1.Siemens AG, ZFE T SN2MuenchenGermany
  2. 2.VacavilleU.S.A.

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