An Introduction to Robust Combinatorial Optimization

An Introduction to Robust Combinatorial Optimization
Author :
Publisher : Springer Nature
Total Pages : 316
Release :
ISBN-10 : 9783031612619
ISBN-13 : 3031612612
Rating : 4/5 (612 Downloads)

Book Synopsis An Introduction to Robust Combinatorial Optimization by : Marc Goerigk

Download or read book An Introduction to Robust Combinatorial Optimization written by Marc Goerigk and published by Springer Nature. This book was released on with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:


An Introduction to Robust Combinatorial Optimization Related Books

An Introduction to Robust Combinatorial Optimization
Language: en
Pages: 316
Authors: Marc Goerigk
Categories:
Type: BOOK - Published: - Publisher: Springer Nature

DOWNLOAD EBOOK

Local Search in Combinatorial Optimization
Language: en
Pages: 530
Authors: Emile H. L. Aarts
Categories: Computers
Type: BOOK - Published: 2003-08-03 - Publisher: Princeton University Press

DOWNLOAD EBOOK

1. Introduction -- 2. Computational complexity -- 3. Local improvement on discrete structures -- 4. Simulated annealing -- 5. Tabu search -- 6. Genetic algorith
A First Course in Combinatorial Optimization
Language: en
Pages: 232
Authors: Jon Lee
Categories: Business & Economics
Type: BOOK - Published: 2004-02-09 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A First Course in Combinatorial Optimization is a text for a one-semester introductory graduate-level course for students of operations research, mathematics, a
Recoverable Robustness in Combinatorial Optimization
Language: en
Pages: 154
Authors: Christina Büsing
Categories: Kombinatorische Optimierung / swd / (DE-101)040318265 / (DE-588c)4031826-6
Type: BOOK - Published: 2011 - Publisher:

DOWNLOAD EBOOK

Robust Discrete Optimization and Its Applications
Language: en
Pages: 373
Authors: Panos Kouvelis
Categories: Mathematics
Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applicat