Cambridge Series in Chemical Engineering / Advanced Optimization for Process Systems Engineering
(Sprache: Englisch)
A unique text covering both basic and advanced concepts of optimization theory and methods for process systems engineers.
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Produktinformationen zu „Cambridge Series in Chemical Engineering / Advanced Optimization for Process Systems Engineering “
A unique text covering both basic and advanced concepts of optimization theory and methods for process systems engineers.
Klappentext zu „Cambridge Series in Chemical Engineering / Advanced Optimization for Process Systems Engineering “
Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential text for single-semester, graduate courses in process systems engineering in departments of chemical engineering.
Inhaltsverzeichnis zu „Cambridge Series in Chemical Engineering / Advanced Optimization for Process Systems Engineering “
Preface; 1. Optimization in process systems engineering; 2. Solving nonlinear equations; 3. Basic theoretical concepts in optimization; 4. Nonlinear programming algorithms; 5. Linear programming; 6. Mixed-integer programming models; 7. Systematic modeling of constraints with logic; 8. Mixed-integer linear programming; 9 Mixed-integer nonlinear programming; 10. Generalized disjunctive programming; 11. Constraint programming; 12. Nonconvex optimization; 13. Lagrangean decomposition; 14. Stochastic programming; 15. Flexibility analysis; Appendix A. Modeling systems and optimization software; Appendix B. Optimization models for process systems engineering; References; Index.
Autoren-Porträt von Ignacio E. Grossmann
Grossmann, Ignacio E. Ignacio E. Grossmann is the R. R. Dean University Professor of Chemical Engineering at Carnegie Mellon University, and Director of the Center for Advanced Process Decision-making. He is a member of the National Academy of Engineering.
Bibliographische Angaben
- Autor: Ignacio E. Grossmann
- 2021, 102 Seiten, Maße: 19,4 x 25,2 cm, Gebunden, Englisch
- Verlag: Cambridge University Press
- ISBN-10: 1108831656
- ISBN-13: 9781108831659
- Erscheinungsdatum: 03.08.2021
Sprache:
Englisch
Pressezitat
'Authored by Ignacio Grossmann, the creator and key developer of the field of mixed integer nonlinear programming, this outstanding textbook provides a thorough and comprehensive treatment of fundamental concepts, optimization models and effective solution strategies for discrete and continuous optimization. It is an essential, 'must-have' reference for all students, researchers and practitioners in process systems engineering.' Lorenz Biegler, Carnegie Mellon University
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