Ignacio E. Grossmann

Advanced Optimization for Process Systems Engineering

• Gebundenes Buch

Produktbeschreibung

A unique text covering basic and advanced concepts of optimization theory and methods for process systems engineers. With examples illustrating key concepts and algorithms, and exercises involving theoretical derivations, numerical problems and modeling systems, it is ideal for single-semester, graduate courses in process systems engineering.

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Produktdetails

• Cambridge Series in Chemical Engineering
• Verlag: Cambridge University Press
• Seitenzahl: 102
• Erscheinungstermin: 25. März 2021
• Englisch
• Abmessung: 251mm x 191mm x 15mm
• Gewicht: 600g
• ISBN-13: 9781108831659
• ISBN-10: 1108831656
• Artikelnr.: 60587580

Autorenporträt

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.

Inhaltsangabe

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.

Rezensionen

'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