Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming
This book presents a comprehensive description of theory, algorithms and software for solving nonconvex mixed integer nonlinear programs (MINLP). The main focus is on deterministic global optimization methods, which play a very important role in integer linear programming, and are used only recently...
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Format: | eBook |
Language: | English |
Published: |
Basel
Birkhäuser
2005, 2005
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Edition: | 1st ed. 2005 |
Series: | International Series of Numerical Mathematics
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Basic Concepts
- Problem Formulations
- Convex and Lagrangian Relaxations
- Decomposition Methods
- Semidefinite Relaxations
- Convex Underestimators
- Cuts, Lower Bounds and Box Reduction
- Local and Global Optimality Criteria
- Adaptive Discretization of Infinite Dimensional MINLPs
- Algorithms
- Overview of Global Optimization Methods
- Deformation Heuristics
- Rounding, Partitioning and Lagrangian Heuristics
- Branch-Cut-and-Price Algorithms
- LaGO — An Object-Oriented Library for Solving MINLPs