Retrospective on optimization

In this paper, we provide a general classification of mathematical optimization problems, followed by a matrix of applications that shows the areas in which these problems have been typically applied in process systems engineering. We then provide a review of solution methods of the major types of o...

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Veröffentlicht in:Computers & chemical engineering Jg. 28; H. 8; S. 1169 - 1192
Hauptverfasser: Biegler, Lorenz T., Grossmann, Ignacio E.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.07.2004
Schlagworte:
Dynamic optimization
Linear programming
Mixed integer nonlinear programming
Nonlinear programming
Process optimization
Stochastic optimization
Linear programming
Process optimization
Mixed integer nonlinear programming
Nonlinear programming
Stochastic optimization
Dynamic optimization
ISSN:0098-1354, 1873-4375
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:In this paper, we provide a general classification of mathematical optimization problems, followed by a matrix of applications that shows the areas in which these problems have been typically applied in process systems engineering. We then provide a review of solution methods of the major types of optimization problems for continuous and discrete variable optimization, particularly nonlinear and mixed-integer nonlinear programming (MINLP). We also review their extensions to dynamic optimization and optimization under uncertainty. While these areas are still subject to significant research efforts, the emphasis in this paper is on major developments that have taken place over the last 25 years.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2003.11.003