
Computational Combinatorial Optimization
Optimal or Provably Near-Optimal Solutions
Springer (Publisher)
Published on 21. November 2001
Book
Paperback/Softback
X, 310 pages
978-3-540-42877-0 (ISBN)
Description
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.
More details
Series
Edition
2001 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Professional/practitioner
Illustrations
X, 310 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 18 mm
Weight
487 gr
ISBN-13
978-3-540-42877-0 (9783540428770)
DOI
10.1007/3-540-45586-8
Schweitzer Classification
Other editions
Additional editions

Michael Jünger | Denis Naddef
Computational Combinatorial Optimization
Optimal or Provably Near-Optimal Solutions
E-Book
01/2001
Springer
€53.49
Available for download
Content
General Mixed Integer Programming: Computational Issues for Branch-and-Cut Algorithms.- Projection and Lifting in Combinatorial Optimization.- Mathematical Programming Models and Formulations for Deterministic Production Planning Problems.- Lagrangian Relaxation.- Branch-and-Cut Algorithms for Combinatorial Optimization and Their Implementation in ABACUS.- Branch, Cut, and Price: Sequential and Parallel.- TSP Cuts Which Do Not Conform to the Template Paradigm.