Integer Programming

Höfundur Laurence A. Wolsey

Útgefandi Wiley Global Research (STMS)

Snið ePub

Print ISBN 9781119606536

Útgáfa 2

Útgáfuár 2020

13.090 kr.

Description

Efnisyfirlit

  • Cover
  • Preface to the Second Edition
  • Preface to the First Edition
  • Intended Audience
  • What and How
  • Abbreviations and Notation
  • About the Companion Website
  • 1 Formulations
  • 1.1 Introduction
  • 1.2 What Is an Integer Program?
  • 1.3 Formulating IPs and BIPs
  • 1.4 The Combinatorial Explosion
  • 1.5 Mixed Integer Formulations
  • 1.6 Alternative Formulations
  • 1.7 Good and Ideal Formulations
  • 1.8 Notes
  • 1.9 Exercises
  • 2 Optimality, Relaxation, and Bounds
  • 2.1 Optimality and Relaxation
  • 2.2 Linear Programming Relaxations
  • 2.3 Combinatorial Relaxations
  • 2.4 Lagrangian Relaxation
  • 2.5 Duality
  • 2.6 Linear Programming and Polyhedra
  • 2.7 Primal Bounds: Greedy and Local Search
  • 2.8 Notes
  • 2.9 Exercises
  • 3 Well‐Solved Problems
  • 3.1 Properties of Easy Problems
  • 3.2 IPs with Totally Unimodular Matrices
  • 3.3 Minimum Cost Network Flows
  • 3.4 Special Minimum Cost Flows
  • 3.5 Optimal Trees
  • 3.6 Submodularity and Matroids
  • 3.7 Two Harder Network Flow Problems*
  • 3.8 Notes
  • 3.9 Exercises
  • 4 Matchings and Assignments
  • 4.1 Augmenting Paths and Optimality
  • 4.2 Bipartite Maximum Cardinality Matching
  • 4.3 The Assignment Problem
  • 4.4 Matchings in Nonbipartite Graphs
  • 4.5 Notes
  • 4.6 Exercises
  • 5 Dynamic Programming
  • 5.1 Some Motivation: Shortest Paths
  • 5.2 Uncapacitated Lot‐Sizing
  • 5.3 An Optimal Subtree of a Tree
  • 5.4 Knapsack Problems
  • 5.5 The Cutting Stock Problem*
  • 5.6 Notes
  • 5.7 Exercises
  • 6 Complexity and Problem Reductions
  • 6.1 Complexity
  • 6.2 Decision Problems, and Classes and
  • 6.3 Polynomial Reduction and the Class
  • 6.4 Consequences of or
  • 6.5 Optimization and Separation
  • 6.6 The Complexity of Extended Formulations
  • 6.7 Worst‐Case Analysis of Heuristics
  • 6.8 Notes
  • 6.9 Exercises
  • 7 Branch and Bound
  • 7.1 Divide and Conquer
  • 7.2 Implicit Enumeration
  • 7.3 Branch and Bound: an Example
  • 7.4 LP‐Based Branch and Bound
  • 7.5 Using a Branch‐and‐Bound/Cut System
  • 7.6 Preprocessing or Presolve
  • 7.7 Notes
  • 7.8 Exercises
  • 8 Cutting Plane Algorithms
  • 8.1 Introduction
  • 8.2 Some Simple Valid Inequalities
  • 8.3 Valid Inequalities
  • 8.4 A Priori Addition of Constraints
  • 8.5 Automatic Reformulation or Cutting Plane Algorithms
  • 8.6 Gomory’s Fractional Cutting Plane Algorithm
  • 8.7 Mixed Integer Cuts
  • 8.8 Disjunctive Inequalities and Lift‐and‐Project
  • 8.9 Notes
  • 8.10 Exercises
  • 9 Strong Valid Inequalities
  • 9.1 Introduction
  • 9.2 Strong Inequalities
  • 9.3 0–1 Knapsack Inequalities
  • 9.4 Mixed 0–1 Inequalities
  • 9.5 The Optimal Subtour Problem
  • 9.6 Branch‐and‐Cut
  • 9.7 Notes
  • 9.8 Exercises
  • 10 Lagrangian Duality
  • 10.1 Lagrangian Relaxation
  • 10.2 The Strength of the Lagrangian Dual
  • 10.3 Solving the Lagrangian Dual
  • 10.4 Lagrangian Heuristics
  • 10.5 Choosing a Lagrangian Dual
  • 10.6 Notes
  • 10.7 Exercises
  • 11 Column (and Row) Generation Algorithms
  • 11.1 Introduction
  • 11.2 The Dantzig–Wolfe Reformulation of an IP
  • 11.3 Solving the LP Master Problem: Column Generation
  • 11.4 Solving the Master Problem: Branch‐and‐Price
  • 11.5 Problem Variants
  • 11.6 Computational Issues
  • 11.7 Branch‐Cut‐and‐Price: An Example*
  • 11.8 Notes
  • 11.9 Exercises
  • 12 Benders’ Algorithm
  • 12.1 Introduction
  • 12.2 Benders’ Reformulation
  • 12.3 Benders’ with Multiple Subproblems
  • 12.4 Solving the Linear Programming Subproblems
  • 12.5 Integer Subproblems: Basic Algorithms*
  • 12.6 Notes
  • 12.7 Exercises
  • 13 Primal Heuristics
  • 13.1 Introduction
  • 13.2 Greedy and Local Search Revisited
  • 13.3 Improved Local Search Heuristics
  • 13.4 Heuristics Inside MIP Solvers
  • 13.5 User‐Defined MIP heuristics
  • 13.6 Notes
  • 13.7 Exercises
  • 14 From Theory to Solutions
  • 14.1 Introduction
  • 14.2 Software for Solving Integer Programs
  • 14.3 How Do We Find an Improved Formulation?
  • 14.4 Multi‐item Single Machine Lot‐Sizing
  • 14.5 A Multiplexer Assignment Problem
  • 14.6 Integer Programming and Machine Learning*
  • 14.7 Notes
  • 14.8 Exercises
  • References
  • Index
  • Integer Programming: 2nd Edition
  • Solutions to Certain Exercises in IP Book
  • Solutions to Certain Exercises in Chapter 1
  • Solutions to Certain Exercises in Chapter 2
  • Solutions to Certain Exercises in Chapter 3
  • Solutions to Certain Exercises in Chapter 4
  • Solutions to Certain Exercises in Chapter 5
  • Solutions to Certain Exercises in Chapter 6
  • Solutions to Certain Exercises in Chapter 7
  • Solutions to Certain Exercises in Chapter 8
  • Solutions to Certain Exercises in Chapter 9
  • Solutions to Certain Exercises in Chapter 10
  • Solutions to Certain Exercises in Chapter 11
  • Solutions to Certain Exercises in Chapter 12
  • Solutions to Certain Exercises in Chapter 13
  • Solutions to Certain Exercises in Chapter 14
  • End User License Agreement
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