Journal of Global Optimization

, Volume 43, Issue 2, pp 175–190

Improved scatter search for the global optimization of computationally expensive dynamic models

Authors

    • Instituto de Investigaciones Marinas (C.S.I.C.)Process Engineering Group
  • Emmanuel Vazquez
    • Department of Signal and Electronic Systems, SupélecPlateau de Moulon
  • Julio R. Banga
    • Instituto de Investigaciones Marinas (C.S.I.C.)Process Engineering Group
  • Rafael Martí
    • Departamento de Estadística e Investigación OperativaUniversitat de València
Article

DOI: 10.1007/s10898-007-9172-y

Cite this article as:
Egea, J.A., Vazquez, E., Banga, J.R. et al. J Glob Optim (2009) 43: 175. doi:10.1007/s10898-007-9172-y

Abstract

A new algorithm for global optimization of costly nonlinear continuous problems is presented in this paper. The algorithm is based on the scatter search metaheuristic, which has recently proved to be efficient for solving combinatorial and nonlinear optimization problems. A kriging-based prediction method has been coupled to the main optimization routine in order to discard the evaluation of solutions that are not likely to provide high quality function values. This makes the algorithm suitable for the optimization of computationally costly problems, as is illustrated in its application to two benchmark problems and its comparison with other algorithms.

Keywords

Global optimizationExpensive functionsScatter searchKriging
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© Springer Science+Business Media LLC 2007