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Tytuł artykułu

Simulation-based optimization; methods and practical application

Identyfikatory
Warianty tytułu
Konferencja
Evolutionary Computation and Global Optimization 2006 / National Conference (9 ; 31.05-2.06.2006 ; Murzasichle, Poland)
Języki publikacji
EN
Abstrakty
EN
The paper is concerned with computational research for complex systems. The simulation-based optimization approach, which is widely used in applied science and engineering, is formulated and discussed. The numerical techniques that optimize performance of system by using simulation to evaluate the objective value are reviewed. The focus is on random search and metaheuristics. The practical example - application of simulation optimization to calculate the optimal decisions for controlling the river-basin reservoir system during flood period is presented and discussed.
Rocznik
Tom
Strony
291--300
Opis fizyczny
Bibliogr. 19 poz., tab., rys.
Twórcy
  • Warsaw University of Technology, Institute of Control and Computation Engineering, Warsaw, Poland, ens@ia.pw.edu.pl
Bibliografia
  • [1] M.M. Ali and C. Storey. Modified controlled random search algorithms. International Journal of Computer Mathematics, 54:229-235, 1995.
  • [2] M.M. Ali, A. Törn and S. Vittanen. A numerical comparison of some modified controlled random search algorithms. Journal of Global Optimization, 11:377-385, 1997.
  • [3] J. April, F. Glover, J.P. Kelley and M. Laguna. Practical introduction to simulation optimization. In Proceedings of the 2003 Winter Simulation Conference, pages 71-78, 2003.
  • [4] T. Baeck, D.B. Fogel and Z. Michalewicz. Evolutionary computation 2: Advanced algorithms and operators. Institute of Physics Publishing, Bristol, UK, 2000.
  • [5] J. Banks, editor. Handbook of simulation. John Wiley & Sons, Inc. New York, 1998.
  • [6] A. Dekkers and E. Aarts. Global optimization and simulated annealing. Mathematical Programming, 50:367-393, 1999.
  • [7] F. Glove. Tabu search - part 1 and part 2. ORSA Journal on Computing, 1, 2:190-206, 4-31, 1989, 1990.
  • [8] D.E. Goldberg. Genetic algorithms in search, optimization and machine learning. Addison-Wesley Pub. Co., Massachusetts, 1989.
  • [9] D.E. Goldberg. The design of innovation. Kluwer Academic Publishers, Dordrecht, 2002.
  • [10] R. Horst and P.M. Pardalos. Handbook of global optimization. Kluwer Academic Publishers, Dordrecht, 1995.
  • [11] Z. Michalewicz. Genetic algorithms + data structures = evolution programs. Springer-Verlag, Berlin Heidelberg, 1996.
  • [12] Z. Michalewicz and D.B. Fogel. How to solve it: Modern heuristics. Springer-Verlag, New York, 2000.
  • [13] E. Niewiadomska-Szynkiewicz. Pareallel global optimization for optimal flood control. Acta Geophysica Polonica, 47:93-109, 1999.
  • [14] E. Niewiadomska-Szynkiewicz. Computer simulation of flood operation in multireservoir systems. Simulation, 80:101-116, 2004.
  • [15] E. Niewiadomska-Szynkiewicz, K. Malinowski and A. Karbowski. Predictive methods for real time control of flood operation of a multireservoir system - methodology and comparative study. Water Resources Research, 32:2885-2895, 1996.
  • [16] W.H. Press, S.A. Tukolsky, W.T. Vetterling and B.P. Flannery. Numerical recipes in C. The art of scientific computing. Cambridge University Press, Cambridge, 1992.
  • [17] W.L. Price. Global optimization algorithms for a cad workstations. Journal of Optimization Theory and Applications, 55:133-146, 1987.
  • [18] J.C. Spall. Introduction to stochastic search and optimization. John Wiley & Sons, New Jersey, 2003.
  • [19] A. Törn and A. Žilinskas. Global optimization. Springer-Verlag, Berlin, 1989.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA9-0052-0031
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