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Optimization by GRASP

Name: Optimization by GRASP
Brand: Springer-Verlag New York Inc.
SKU: 9781493965281
Price: 352.23 PLN
Availability: InStock

Greedy Randomized Adaptive Search Procedures

Autor: Resende

Język:

Oprawa: Twarda

Wydawca: Springer-Verlag New York Inc.

Dostępność: Dostępna u dostawcy

Wysyłamy za 10-13 dni

352.23 zł

This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristi...

Informacje o książce

Autor

Resende

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2016

strony

312

EAN

9781493965281

ISBN

149396528X

Enbook ID

13495056

Wydawca

Springer-Verlag New York Inc.

Waga

652

Wymiary

245 x 167 x 24

Pełny opis

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 GRASP and 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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Optimization by GRASP

Greedy Randomized Adaptive Search Procedures

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