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161103 ||| eng |
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|a 9781493965304
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|a Resende, Mauricio G.C.
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| 245 |
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|a Optimization by GRASP
|h Elektronische Ressource
|b Greedy Randomized Adaptive Search Procedures
|c by Mauricio G.C. Resende, Celso C. Ribeiro
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| 250 |
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|a 1st ed. 2016
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| 260 |
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|a New York, NY
|b Springer New York
|c 2016, 2016
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| 300 |
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|a XX, 312 p. 173 illus., 117 illus. in color
|b online resource
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|a Foreword -- Preface -- 1. Introduction -- 2. A short tour of combinatorial optimization and computational complexity -- 3. Solution construction and greedy algorithms -- 4. Local search -- 5. GRASP: The basic heuristic -- 6. Runtime distributions -- 7. GRASP: extended construction heuristics -- 8. Path-relinking -- 9. GRASP with Path-relinking -- 10. Parallel GRASP heuristics -- 11. GRASP for continuous optimization -- 12. Case studies -- References -- Index
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| 653 |
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|a Operations research
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| 653 |
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|a Industrial engineering
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| 653 |
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|a Computer science / Mathematics
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| 653 |
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|a Discrete Mathematics in Computer Science
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Computational Mathematics and Numerical Analysis
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| 653 |
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|a Mathematics / Data processing
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| 653 |
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|a Industrial and Production Engineering
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Discrete mathematics
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| 653 |
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|a Operations Research and Decision Theory
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| 653 |
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|a Production engineering
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| 700 |
1 |
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|a Ribeiro, Celso C.
|e [author]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
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|a 10.1007/978-1-4939-6530-4
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| 856 |
4 |
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|u https://doi.org/10.1007/978-1-4939-6530-4?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 518
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| 520 |
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|a 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
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