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Titlebook: Optimization by GRASP; Greedy Randomized Ad Mauricio G.C. Resende,Celso C. Ribeiro Textbook 2016 Springer Science+Business Media New York 2

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书目名称Optimization by GRASP
副标题Greedy Randomized Ad
编辑Mauricio G.C. Resende,Celso C. Ribeiro
视频video
概述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 eff
图书封面Titlebook: Optimization by GRASP; Greedy Randomized Ad Mauricio G.C. Resende,Celso C. Ribeiro Textbook 2016 Springer Science+Business Media New York 2
描述.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 algorit
出版日期Textbook 2016
关键词GRASP; GRASP optimization; combinatorial optimization; discrete mathematics; metaheuristics; Greedy Rando
版次1
doihttps://doi.org/10.1007/978-1-4939-6530-4
isbn_softcover978-1-4939-8227-1
isbn_ebook978-1-4939-6530-4
copyrightSpringer Science+Business Media New York 2016
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GRASP: The basic heuristic,i-greedy multistart procedures and show how solutions produced by both procedures differ. The hybridization of a semi-greedy procedure with a local search method constitutes a GRASP heuristic. The chapter concludes with some implementation details, including stopping criteria.
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Case studies,s are for 2-path network design, graph planarization, unsplittable multicommodity flows, and maximum cut in a graph. The key point here is not to show numerical results or compare these GRASP heuristics with other approaches, but instead simply show how to customize the GRASP metaheuristic for each particular problem.
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Mauricio G. C. Resende,Celso C. RibeiroRealität, die physikalische Wirklichkeit, an. Das ist aber fast nirgends so weit gefehlt wie bei der Analyse unserer Fortbewegung. Hier schon zu Beginn und im Weiteren kann modernes Herumbewegen von Personen und Waren nur erklärt werden, wenn die Bilder und Vorstellungen in den Köpfen der Menschen i
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Introduction,number of fundamental combinatorial optimization problems that will be revisited along the next chapters of this book. We also contrast exact and approximate solution methods and trace a brief history of approximate algorithms (or heuristics) from A. to metaheuristics, going through greedy algorithm
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