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Deterministic Global Optimization :
Theory, Algorithms and Applications
Christodoulos A. Floudas
Department of Chemical Engineering
Princeton University
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Kluwer Academic Publishers
Nonconvex Optimization and Its Applications
Volume 37, 760 pp.
ISBN 0-7923-6014-1 (Hardbound)
http://www.wkap.nl/series.htm/NOIA
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This book provides a unified and insightful treatment
of deterministic global optimization. It introduces
theoretical and algorithmic advances that
address the computation and
characterization of global optima,
determine valid lower and upper bounds on the global minima and maxima,
and enclose all solutions of nonlinear
constrained systems of equations.
Among its special features, the book :
- Introduces the fundamentals of
deterministic global optimization
- Provides a thorough treatment of decomposition based
global optimization approaches for biconvex and bilinear problems
- Covers global optimization methods for generalized geometric
programming problems
- Presents in depth global optimization algorithms for general
twice continuously differentiable nonlinear problems
- Provides a detailed treatment of global optimization methods
for mixed-integer nonlinear problems
- Develops global optimization approaches for the
enclosure of all solutions of nonlinear constrained systems of equations
- Includes many important applications from
process design, synthesis, control, and operations,
phase equilibrium, design under uncertainty, parameter estimation,
azeotrope prediction, structure prediction in clusters and molecules,
protein folding, and peptide docking .
Audience
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This book can be used as a textbook in graduate level courses
and as a desk reference for researchers in
all branches of engineering and applied science,
applied mathematics, industrial engineering,
operations research, computer science, economics, computational
chemistry and molecular biology.
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Table of Contents
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Preface
Chapter 1 : Introduction
Chapter 2 : Basic Concepts of Global Optimization
Part I - Biconvex and Bilinear Problems
Chapter 3 : The GOP Primal Relaxed Dual Decomposition Approach: Theory
Chapter 4 : The GOP Approach : Implementation and Computational Studies
Chapter 5 : The GOP Approach in Bilevel Linear and Quadratic problems
Chapter 6 : The GOP Approach in Phase and Chemical Equilibrium
Chapter 7 : The GOP Approach - Distributed Implementation
Part II - Signomial Problems
Chapter 8 : Generalized Geometric Programming : Theory
Chapter 9 : Generalized Geometric Programming : Computational Studies
Part III - Towards Twice Differentiable NLPs
Chapter 10 : From Biconvex to General Twice Differentiable NLPs
Chapter 11 : The aBB for Box-Constrained NLPs
Chapter 12 : The aBB for General Constrained NLPs : Theory
Chapter 13 : Computational Studies of the aBB Approach
Chapter 14 : Global Optimization in Microclusters
Chapter 15 : The aBB Approach in Molecular Structure Prediction
Chapter 16 : The aBB Approach in Protein Folding
Chapter 17 : The aBB Approach in Peptide Docking
Chapter 18 : The aBB Approach in Batch Design under Uncertainty
Chapter 19 : The aBB Approach in Parameter Estimation
Part IV - Nonlinear and Mixed Integer Optimization
Chapter 20 : Introduction
Chapter 21 : The SMIN-aBB Approach : Theory and Computations
Chapter 22 : The GMIN-aBB Approach : Theory and Computations
Part V - Nonlinear Constrained Systems of Equations
Chapter 23 : All Solutions of Nonlinear Constrained Systems of Equations
Chapter 24 : Locating All Homogeneous Azeotropes
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Professor C.A. Floudas Tel : 609-258-4595 (Office)
Department of Chemical Engineering Fax : 609-258-2391 (Office)
Princeton University Fax : 609-258-0211 (Department)
Princeton, N.J. 08544-5263 e-mail : [log in to unmask]
USA
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Homepage : http://titan.princeton.edu
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