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

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

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.

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computational optimization and applications 2014-03, Vol.57 (2), p.469-492
Hauptverfasser: Easterling, David R., Watson, Layne T., Madigan, Michael L., Castle, Brent S., Trosset, Michael W.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Approximation
Biomechanics
Computer science
Convex and Discrete Geometry
Generators
Integer programming
Management Science
Mathematical analysis
Mathematical models
Mathematics
Mathematics and Statistics
Minima
Musculoskeletal system
Operations Research
Operations Research/Decision Theory
Optimization
Optimization algorithms
Optimization techniques
Packages
Simulated annealing
Statistics
Stochasticity
Studies
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:0926-6003
1573-2894
DOI:10.1007/s10589-013-9592-1