Yazar
Pinter, Janos D., Horvath, Z.
Basım Tarihi
2013-09
Basım Yeri
-
Springer Science+Business Media
Konu
Nonlinear optimization under resource constraints, Metamodel, Experimental design, Latin hypercube design (LHD), Regularly spaced sampling LHD strategies, RSS software implementation, LGO solver suite for nonlinear optimization, MathOptimizer Professional (LGO linked to Mathematica), Illustrative numerical results
Tür
Süreli Yayın
Dil
İngilizce
Dijital
Evet
Yazma
Hayır
Kütüphane
Özyeğin Üniversitesi
Demirbaş Numarası
1573-2916
Kayıt Numarası
21b24880-59c9-487f-b1bd-2675edddb2f3
Lokasyon
Industrial Engineering
Tarih
2013-09
Notlar
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin
In many real-world applications of optimization, the underlying descriptive system model is defined by computationally expensive functions: simulation modules, numerical models and other “black box” model components are typical examples. In such cases, the model development and optimization team often has to rely on optimization carried out under severe resource constraints. To address this important issue, recently a Regularly Spaced Sampling (RSS) module has been added to the Lipschitz Global Optimizer (LGO) solver suite. RSS generates non-collapsing space filling designs, and produces corresponding solution estimates: this information is passed along to LGO for refinement within the given resource (function evaluation and/or runtime) limitations. Obviously, the quality of the solution obtained will essentially depend both on model instance difficulty and on the admissible computational effort. In spite of this general caveat, our results based on solving a selection of non-trivial global optimization test problems suggest that even a moderate amount of well-placed sampling effort enhanced by limited optimization can lead at least to reasonable or even to high quality results. Our numerical tests also indicate that LGO’s overall efficiency is often increased by using RSS as a presolver, both in resource-constrained and in completed LGO runs.
DOI
10.1007/s10898-012-9882-7
Cilt
57
