Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming

Authors:

ISBN: 978-3-7643-7238-5 (Print) 978-3-7643-7374-0 (Online)

Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvi

  2. Basic Concepts

    1. Front Matter

      Pages 1-1

    2. No Access

      Book Chapter

      Pages 3-7

      Introduction

    3. No Access

      Book Chapter

      Pages 9-19

      Problem Formulations

    4. No Access

      Book Chapter

      Pages 21-31

      Convex and Lagrangian Relaxations

    5. No Access

      Book Chapter

      Pages 33-53

      Decomposition Methods

    6. No Access

      Book Chapter

      Pages 55-71

      Semidefinite Relaxations

    7. No Access

      Book Chapter

      Pages 73-81

      Convex Underestimators

    8. No Access

      Book Chapter

      Pages 83-97

      Cuts, Lower Bounds and Box Reduction

    9. No Access

      Book Chapter

      Pages 99-111

      Local and Global Optimality Criteria

    10. No Access

      Book Chapter

      Pages 113-118

      Adaptive Discretization of Infinite Dimensional MINLPs

  3. Algorithms

    1. Front Matter

      Pages 119-119

    2. No Access

      Book Chapter

      Pages 121-128

      Overview of Global Optimization Methods

    3. No Access

      Book Chapter

      Pages 129-142

      Deformation Heuristics

    4. No Access

      Book Chapter

      Pages 143-154

      Rounding, Partitioning and Lagrangian Heuristics

    5. No Access

      Book Chapter

      Pages 155-179

      Branch-Cut-and-Price Algorithms

    6. No Access

      Book Chapter

      Pages 181-186

      LaGO — An Object-Oriented Library for Solving MINLPs

  4. Back Matter

    Pages 187-213