Authors:
- First book on GRASP, an optimization technique that has been used all over the world by engineers, optimization specialists, scientists, and more
- Includes a how-to guide on designing efficient and effective GRASP heuristics to solve real-world optimization problems
- Includes an original and innovative introduction to combinatorial optimization and heuristics
- Based on extensive experience teaching GRASP and other metaheuristics to undergraduate and graduate students globally
- Includes a section on case studies describing successful applications of GRASP in practice
- Explores tools for performance evaluation and algorithm comparison which are not explored in other books in the area
- Unified algorithm presentation based on pseudo-codes following the same style throughout the text
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Table of contents (12 chapters)
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Front Matter
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Back Matter
About this book
This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristic that has enjoyed wide success in practice with a broad range of applications to real-world combinatorial optimization problems. The state-of-the-art coverage and carefully crafted pedagogical style lends this book highly accessible as an introductory text not only to GRASP, but also to combinatorial optimization, greedy algorithms, local search, and path-relinking, as well as to heuristics and metaheuristics, in general. The focus is on algorithmic and computational aspects of applied optimization with GRASP with emphasis given to the end-user, providing sufficient information on the broad spectrum of advances in applied optimization with GRASP. For the more advanced reader, chapters on hybridization with path-relinking and parallel and continuous GRASP present these topics in a clear and concise fashion. Additionally, the book offers a very complete annotated bibliography of GRASPand combinatorial optimization. For the practitioner who needs to solve combinatorial optimization problems, the book provides a chapter with four case studies and implementable templates for all algorithms covered in the text. This book, with its excellent overview of GRASP, will appeal to researchers and practitioners of combinatorial optimization who have a need to find optimal or near optimal solutions to hard combinatorial optimization problems.
Keywords
Reviews
“The book is a comprehensive introduction to the greedy randomized adaptive search procedures (GRASP), first applied to the set covering problems and then to other combinatorial problems. … The book is a very good choice for scientists,students and engineers, introducing to the subject of GRASP … . I strongly recommend this book to both theoreticians and practitionners of OR.” (Marcin Anholcer, zbMATH 1356.90001, 2017)
Authors and Affiliations
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Modeling and Optimization Group (MOP), Amazon.com, Inc., Seattle, USA
Mauricio G.C. Resende
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Instituto de Ciência da Computação, Universidade Federal Fluminense, Niterói, Brazil
Celso C. Ribeiro
Bibliographic Information
Book Title: Optimization by GRASP
Book Subtitle: Greedy Randomized Adaptive Search Procedures
Authors: Mauricio G.C. Resende, Celso C. Ribeiro
DOI: https://doi.org/10.1007/978-1-4939-6530-4
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media New York 2016
Hardcover ISBN: 978-1-4939-6528-1
Softcover ISBN: 978-1-4939-8227-1
eBook ISBN: 978-1-4939-6530-4
Edition Number: 1
Number of Pages: XX, 312
Number of Illustrations: 56 b/w illustrations, 117 illustrations in colour
Topics: Computational Mathematics and Numerical Analysis, Discrete Mathematics in Computer Science, Operations Research/Decision Theory, Industrial and Production Engineering, Artificial Intelligence