Nonlinear Programming
Concepts, Algorithms, and Applications to Chemical Processes
Will be published approx. on 30. September 2010
Book
Hardback
415 pages
978-0-89871-702-0 (ISBN)
Description
This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.
Nonlinear Programming shows readers which NLP methods are best suited for specific applications, how large-scale problems should be formulated and what features of these problems should be emphasized, and how existing NLP methods can be extended to exploit specific structures of large-scale optimization models.
Nonlinear Programming shows readers which NLP methods are best suited for specific applications, how large-scale problems should be formulated and what features of these problems should be emphasized, and how existing NLP methods can be extended to exploit specific structures of large-scale optimization models.
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Dimensions
Height: 264 mm
Width: 184 mm
Thickness: 27 mm
Weight
897 gr
ISBN-13
978-0-89871-702-0 (9780898717020)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Lorenz T. Biegler is the Bayer Professor of Chemical Engineering at Carnegie Mellon University and a Fellow of the American Institute of Chemical Engineers. He has authored or coauthored over 200 journal articles and two books. His research interests lie in the field of computer-aided process engineering, including flowsheet optimization, optimization of systems of differential and algebraic equations, reactor network synthesis and algorithms for constrained, nonlinear process control.
Content
Preface
Chapter 1: Introduction to Process Optimization
Chapter 2: Concepts of Unconstrained Optimization
Chapter 3: Newton-Type Methods for Unconstrained Optimization
Chapter 4: Concepts of Constrained Optimization
Chapter 5: Newton Methods for Equality Constrained Optimization
Chapter 6: Numerical Algorithms for Constrained Optimization
Chapter 7: Steady State Process Optimization
Chapter 8: Introduction to Dynamic Process Optimization
Chapter 9: Dynamic Optimization Methods with Embedded DAE Solvers
Chapter 10: Simultaneous Methods for Dynamic Optimization
Chapter 11: Process Optimization with Complementarity Constraints
Bibliography
Index
Chapter 1: Introduction to Process Optimization
Chapter 2: Concepts of Unconstrained Optimization
Chapter 3: Newton-Type Methods for Unconstrained Optimization
Chapter 4: Concepts of Constrained Optimization
Chapter 5: Newton Methods for Equality Constrained Optimization
Chapter 6: Numerical Algorithms for Constrained Optimization
Chapter 7: Steady State Process Optimization
Chapter 8: Introduction to Dynamic Process Optimization
Chapter 9: Dynamic Optimization Methods with Embedded DAE Solvers
Chapter 10: Simultaneous Methods for Dynamic Optimization
Chapter 11: Process Optimization with Complementarity Constraints
Bibliography
Index