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Parallel deterministic and stochastic global minimization of functions with very many minima

Author

Listed:
  • David Easterling
  • Layne Watson
  • Michael Madigan
  • Brent Castle
  • Michael Trosset

Abstract

The optimization of three problems with high dimensionality and many local minima are investigated under five different optimization algorithms: DIRECT, simulated annealing, Spall’s SPSA algorithm, the KNITRO package, and QNSTOP, a new algorithm developed at Indiana University. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • David Easterling & Layne Watson & Michael Madigan & Brent Castle & Michael Trosset, 2014. "Parallel deterministic and stochastic global minimization of functions with very many minima," Computational Optimization and Applications, Springer, vol. 57(2), pages 469-492, March.
    • Handle: RePEc:spr:coopap:v:57:y:2014:i:2:p:469-492
    DOI: 10.1007/s10589-013-9592-1
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    References listed on IDEAS

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    1. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    2. L. Ingber, 1993. "Simulated annealing: Practice versus theory," Lester Ingber Papers 93sa, Lester Ingber.
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    Cited by:

    1. Ubaldo M. García-Palomares, 2020. "Non-monotone derivative-free algorithm for solving optimization models with linear constraints: extensions for solving nonlinearly constrained models via exact penalty methods," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 599-625, October.

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