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Responsible lecturer: Tibor Csendes, university professor (

Assumed preliminary studies:
Linear and Nonlinear Programming


  1. Different forms of global optimization problems, computational complexity, computational complexity relative to the complexity of linear programming.
  2. Problem transformation, transformation to single variable problem
  3. Classification of global optimization problems, classification according to the information applied.
  4. Grid search, random search, dependency on the dimensions of the problem, simulated annealing, genetic, evolutionary, and neural network based methods, their theoretical background.
  5. Stochastic and multistart methods for global optimization, their speeds of convergences and stopping conditions.
  6. Known Lipschitz constant based methods, convergence theorem, single and multi dimensional algorithms.
  7. DC functions, their properties and applications in solving global optimization problems.
  8. Effective solutions for special structure (concave, bilinear, etc.) problems, outer approximation and cut methods.
  9. Interval arithmetic, interval division methods, acceleration tool, interval Newton method, speed of convergence.
  10. Patological problems, symbolic manipulation for global optimization, practical applications, case studies

Required* and proposed literature

Strongin, R.G.: Numerical Methods in Multiextremal Optimization, Nauka, Moscow, 1978 (in Russian).

Dixon, L.C.W., G.P. Szegő (eds.): Towards global optimisation, North-Holland, Amsterdam, 1975.

Dixon, L.C.W., G.P. Szegő (eds.): Towards global optimisation 2, North-Holland, Amsterdam, 1978.

Wilde, D.J.: Globally optimal design. Wiley, New York, 1978.

Dixon, L.C.W., E. Spedicato, G.P. Szegő: Nonlinear Optimization Theory and Algorithms. Birkhä user, Boston, 1980.

Zilinskas, A.: Global Optimization - Axiomatics of Statistical Models, Algorithms and Their Application, Mokslas, Vilnius, 1986 (in Russian).

Pardalos, P.M., J.B. Rosen: Constrained Global Optimization: Algorithms and Applications. Springer-Verlag, Lecture Notes in Computer Science Vol. 268, Berlin, 1987.

Törn, A., A. Zilinskas: Global Optimization, Springer-Verlag, Lecture Notes in Computer Science Vol. 350, Berlin, 1987.*

Ratschek, H., J. Rokne: New computer methods for global optimization, Ellis Horwood, Chichester, 1988.*

Mockus, J.: Bayesian Approach to Global Optimization, Kluwer, Dordrecht, 1989.

Nemhauser, G.L., A.H.G. Rinnooy Kan, M.J. Todd: Optimization, Handbooks in Operations Research and Management Science Vol. 1, North-Holland, Amsterdam, 1989.

Horst, R., H. Tuy: Global Optimization - Deterministic Approaches, Springer-Verlag, Berlin, 1990.*

Floudas, C.A., P.M. Pardalos: A collection of test problems for constrained global optimization algorithms. Lecture Notes in Computer Science Vol. 455. Springer-Verlag, Berlin, 1990.

Zhigljavsky, A.A.: Theory of Global Random Search, Kluwer, Dordrecht, 1991.

Floudas, C.A., P.M. Pardalos: Recent Advances in Global Optimization, Princeton University Press, Princeton, 1992.

Hansen, E.: Global optimization using interval analysis, Marcel Dekker, New York, 1992.

Horst, R., P.M. Pardalos: Handbook of Global Optimization, Kluwer, Dordrecht, 1995.*

Horst, R., P.M. Pardalos, N.V. Thoai: An Introduction to Global Optimization, Kluwer, Dordrecht, 1995.*