Nonlinear and Mixed-Integer Optimization
Fundamentals and Applications
Published on 5. October 1995
475 pages
978-0-19-535655-7 (ISBN)
Description
Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems. The basics of convex analysis and nonlinear optimization are also covered and the elementary concepts of mixed-integer linear optimization are introduced. All chapters have several illustrations and geometrical interpretations of the material as well as suggested problems. Nonlinear and Mixed-Integer Optimization will prove to be an invaluable source--either as a textbook or a reference--for researchers and graduate students interested in continuous and discrete nonlinear optimization issues in engineering design, process synthesis, process operations, applied mathematics, operations research, industrial management, and systems engineering.
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11/1995
Oxford University Press Inc
€166.50
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Content
- Intro
- Contents
- 1. Introduction
- 1.1 Mathematical and Optimization Models
- 1.2 Structure of Nonlinear and Mixed-Integer Optimization Models
- 1.3 Illustrative Applications
- 1.3.1 Binary Distillation Design
- 1.3.2 Retrofit Design of Multiproduct Batch Plants
- 1.3.3 Multicommodity Facility Location-Allocation
- 1.4 Scope of the Book
- PART 1 FUNDAMENTALS OF CONVEX ANALYSIS AND NONLINEAR OPTIMIZATION
- 2. Convex Analysis
- 2.1 Convex Sets
- 2.2 Convex and Concave Functions
- 2.3 Generalizations of Convex and Concave Functions
- 3. Fundamentals of Nonlinear Optimization
- 3.1 Unconstrained Nonlinear Optimization
- 3.2 Constrained Nonlinear Optimization
- 4. Duality Theory
- 4.1 Primal Problem
- 4.2 Dual Problem
- 4.3 Weak and Strong Duality
- 4.4 Duality Gap and Continuity of Perturbation Function
- PART 2 FUNDAMENTALS OF MIXED-INTEGER OPTIMIZATION
- 5. Mixed-Integer Linear Optimization
- 5.1 Motivation
- 5.2 Formulation
- 5.3 Branch and Bound Method
- 6. Mixed-Integer Nonlinear Optimization
- 6.1 Motivation
- 6.2 Formulation
- 6.3 Generalized Benders Decomposition, GBD
- 6.4 Outer Approximations, OA
- 6.5 Outer Approximation with Equality Relaxation, OA/ER
- 6.6 Outer Approximation with Equality Relaxation and Augmented Penalty, OA/ER/AP
- 6.7 Generalized Outer Approximation, GOA
- 6.8 Comparison of GBD and OA-based Algorithms
- 6.9 Generalized Cross Decomposition, GCD
- PART 3 APPLICATIONS IN PROCESS SYNTHESIS
- 7. Process Synthesis
- 7.1 Introduction
- 7.2 Definition
- 7.3 Approaches in Process Synthesis
- 7.4 Optimization Approach in Process Synthesis
- 7.5 Application Areas
- 8. Heat Exchanger Network Synthesis
- 8.1 Introduction
- 8.2 Problem Statement
- 8.3 Targets for HEN Synthesis
- 8.4. Decomposition-based HEN Synthesis Approaches
- 8.5 Simultaneous HEN Synthesis Approaches
- 9. Distillation-based Separation Systems Synthesis
- 9.1 Introduction
- 9.2 Synthesis of Heat-integrated Sharp Distillation Sequences
- 9.3 Synthesis of Nonsharp Distillation Sequences
- 10. Synthesis of Reactor Networks and Reactor-Separator-Recycle Systems
- 10.1 Introduction
- 10.2 Synthesis of Isothermal Reactor Networks
- 10.3 Synthesis of Reactor-Separator-Recycle Systems
- Bibliography
- Index
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- Y
- Z
