Stochastic Approach to Global Optimization at a Glance

  • Stefan Schäffler
Part of the Springer Series in Operations Research and Financial Engineering book series (ORFE)


Genetic Algorithm Simulated Annealing Global Minimization Simulated Annealing Algorithm Global Optimization Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. [HenTót10].
    Hendrix, E.M.T., Tóth, B.: Introduction to Nonlinear and Global Optimization. Springer, Berlin (2010)MATHCrossRefGoogle Scholar
  2. [ZhiŽil08].
    Zhigljavsky, A., Žilinskas, A.: Stochastic Global Optimization. Springer, Berlin (2008)MATHGoogle Scholar
  3. [Kar63].
    Karnopp, D.C.: Random search techniques for optimization problems. Automata 1, 111–121 (1963)CrossRefGoogle Scholar
  4. [Zhi91].
    Zhigljavsky, A.: Theory of Global Random Search. Kluwer, Dordrecht (1991)CrossRefGoogle Scholar
  5. [Bul.etal03].
    Bulger, D., Baritompa, W.P., Wood, G.R.: Implementing pure adaptive search with Grover’s quantum algorithm. JOTA 116, 517–529 (2003)MathSciNetMATHCrossRefGoogle Scholar
  6. [Pat.etal89].
    Patel, N.R., Smith, R.L., Zabinsky, Z.B.: Pure adaptive search in Monte Carlo optimization. Math. Program. 43, 317–328 (1989)MathSciNetMATHCrossRefGoogle Scholar
  7. [Hajek88].
    Hajek, B.: Cooling schedules for optimal annealing. Math. Oper. Res. 13, 311–329 (1988)MathSciNetMATHCrossRefGoogle Scholar
  8. [Holl75].
    Holland, J.H.: Adaption in Natural and Artificial Systems. University of Michigan Press, MI (1975)MATHGoogle Scholar
  9. [KenEber95].
    Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948, Piscataway, NJ (1995)Google Scholar
  10. [LaaAarts87].
    van Laarhoven, P.J.M., Aarts, E.H.L.: Simulated Annealing: Theory and Applications. D. Reidel Publishing Co., Dordrecht (1987)MATHGoogle Scholar
  11. [Mitra.etal86].
    Mitra, D., Romeo, F., Sangiovanni-Vincentelli, A.: Convergence and finite-time behavior of simulated annealing. SIAM J. Contr. Optim. 18, 747–771 (1986)MathSciNetMATHGoogle Scholar
  12. [Sal.etal02].
    Salamon, P., Sibani, P., Frost, R.: Facts, Conjectures, and Improvements for Simulated Annealing. SIAM, Philadelphia (2002)MATHCrossRefGoogle Scholar
  13. [WoodZab02].
    Wood, G.R., Zabinsky, Z.B.: Stochastic adaptive search. In: Pardalos, P., Romeijn, E. (eds.) Handbook of Global Optimization, vol. 2, pp. 231–249. Kluwer, Dordrecht (2002)Google Scholar
  14. [Zab03].
    Zabinsky, Z.B.: Stochastic Adaptive Search for Global Optimization. Kluwer, Dordrecht (2003)MATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Stefan Schäffler
    • 1
  1. 1.Fakultät für Elektro- und Informationstechnik, EIT1Universität der Bundeswehr MünchenNeubibergGermany

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