Computational Combinatorial Optimization : Optimal or Provably Near-Optimal Solutions - Michael JÃ¼nger

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Computational Combinatorial Optimization

Optimal or Provably Near-Optimal Solutions

By: Michael JÃ¼nger (Editor), Denis Naddef (Editor)

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Paperback | 21 November 2001

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320 Pages

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23.5 x 15.88 x 1.91

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This tutorial contains written versions of seven lectures on Computational Combinatorial Optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modeling are extensively discussed. Applications to prominent combinatorial optimization problems, e.g., in production and transport planning, are treated in many places; in particular, the book contains a state-of-the-art account of the most successful techniques for solving the traveling salesman problem to optimality.

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General Mixed Integer Programming: Computational Issues for Branch-and-Cut Algorithms	p. 1
Projection and Lifting in Combinatorial Optimization	p. 26
Mathematical Programming Models and Formulations for Deterministic Production Planning Problems	p. 57
Lagrangian Relaxation	p. 112
Branch-and-Cut Algorithms for Combinatorial Optimization and Their Implementation in ABACUS	p. 157
Branch, Cut, and Price: Sequential and Parallel	p. 223
TSP Cuts Which Do Not Conform to the Template Paradigm	p. 261
Author Index	p. 305
Table of Contents provided by Publisher. All Rights Reserved.

Computational Combinatorial Optimization

Optimal or Provably Near-Optimal Solutions

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

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