Handbook of Approximation Algorithms and Metaheuristics - Info and Reading Options
By Teofilo F. Gonzalez


"Handbook of Approximation Algorithms and Metaheuristics" was published by Chapman & Hall/CRC Press in 2007 - Boca Raton, the book is classified in Computers genre, it has 1 pages and the language of the book is English.
“Handbook of Approximation Algorithms and Metaheuristics” Metadata:
- Title: ➤ Handbook of Approximation Algorithms and Metaheuristics
- Author: Teofilo F. Gonzalez
- Language: English
- Number of Pages: 1
- Is Family Friendly: Yes - No Mature Content
- Publisher: Chapman & Hall/CRC Press
- Publish Date: 2007
- Publish Location: Boca Raton
- Genres: Computers
“Handbook of Approximation Algorithms and Metaheuristics” Subjects and Themes:
- Subjects: ➤ Computer algorithms - Mathematical optimization - Mathematics - Handbooks, manuals, etc - Metaheuristics - Heuristic algorithms - Data processing
Edition Specifications:
- Pagination: p. cm.
Edition Identifiers:
- Google Books ID: H5_SsgEACAAJ
- The Open Library ID: OL17567637M - OL18727676W
- Library of Congress Control Number (LCCN): 2007002478
- ISBN-13: 9781584885504
- ISBN-10: 1584885505
- All ISBNs: 1584885505 - 9781584885504
AI-generated Review of “Handbook of Approximation Algorithms and Metaheuristics”:
Snippets and Summary:
Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical applications.
"Handbook of Approximation Algorithms and Metaheuristics" Description:
Google Books:
Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical applications. It is the first book to comprehensively study both approximation algorithms and metaheuristics. Starting with basic approaches, the handbook presents the methodologies to design and analyze efficient approximation algorithms for a large class of problems, and to establish inapproximability results for another class of problems. It also discusses local search, neural networks, and metaheuristics, as well as multiobjective problems, sensitivity analysis, and stability. After laying this foundation, the book applies the methodologies to classical problems in combinatorial optimization, computational geometry, and graph problems. In addition, it explores large-scale and emerging applications in networks, bioinformatics, VLSI, game theory, and data analysis. Undoubtedly sparking further developments in the field, this handbook provides the essential techniques to apply approximation algorithms and metaheuristics to a wide range of problems in computer science, operations research, computer engineering, and economics. Armed with this information, researchers can design and analyze efficient algorithms to generate near-optimal solutions for a wide range of computational intractable problems.
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