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Algorithm Portfolios : Advances, Applications, and Challenges / by Dimitris Souravlias, Konstantinos E. Parsopoulos, Ilias S. Kotsireas, Panos M. Pardalos
(SpringerBriefs in Optimization. ISSN:2191575X)

1st ed. 2021.
出版者 (Cham : Springer International Publishing : Imprint: Springer)
出版年 2021
本文言語 英語
大きさ XIV, 92 p. 5 illus : online resource
著者標目 *Souravlias, Dimitris author
Parsopoulos, Konstantinos E author
Kotsireas, Ilias S author
Pardalos, Panos M author
SpringerLink (Online service)
件 名 LCSH:Operations research
LCSH:Management science
LCSH:Algorithms
LCSH:Microprogramming 
LCSH:Discrete mathematics
FREE:Operations Research, Management Science
FREE:Algorithms
FREE:Control Structures and Microprogramming
FREE:Discrete Mathematics
一般注記 1. Metaheuristic optimization algorithms -- 2. Algorithm portfolios -- 3. Selection of constituent algorithms -- 4. Allocation of computation resources -- 5. Sequential and parallel models -- 6. Recent applications -- 7. Epilogue -- References
This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field
HTTP:URL=https://doi.org/10.1007/978-3-030-68514-0
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電子ブック オンライン 電子ブック

Springer eBooks 9783030685140
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EB00234266

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データ種別 電子ブック
分 類 LCC:T57.6-57.97
LCC:T55.4-60.8
DC23:003
書誌ID 4000135457
ISBN 9783030685140

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