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Algorithm portfolios = advances, app...

Souravlias, Dimitris.

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Algorithm portfolios = advances, applications, and challenges /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Algorithm portfolios/ by Dimitris Souravlias ... [et al.].
Reminder of title:	advances, applications, and challenges /
other author:	Souravlias, Dimitris.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xiv, 92 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Algorithms. -
Online resource:	https://doi.org/10.1007/978-3-030-68514-0
ISBN:	9783030685140

Algorithm portfolios = advances, applications, and challenges /
Algorithm portfoliosadvances, applications, and challenges /[electronic resource] :by Dimitris Souravlias ... [et al.]. - Cham :Springer International Publishing :2021. - xiv, 92 p. :ill., digital ;24 cm. - SpringerBriefs in optimization,2190-8354. - SpringerBriefs in optimization..

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.

ISBN: 9783030685140

Standard No.: 10.1007/978-3-030-68514-0doiSubjects--Topical Terms:

536374
Algorithms.

LC Class. No.: QA9.58

Dewey Class. No.: 518.1

Algorithm portfolios = advances, applications, and challenges /
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245 0 0 $a Algorithm portfolios $h [electronic resource] : $b advances, applications, and challenges / $c by Dimitris Souravlias ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xiv, 92 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in optimization, $x 2190-8354
505 0 $a 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.
520 $a 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.
650 0 $a Algorithms. $3 536374
650 0 $a Mathematical optimization. $3 517763
650 1 4 $a Operations Research, Management Science. $3 1532996
650 2 4 $a Control Structures and Microprogramming. $3 895886
650 2 4 $a Discrete Mathematics. $3 1569938
700 1 $a Souravlias, Dimitris. $3 3493233
710 2 $a SpringerLink (Online service) $3 836513
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830 0 $a SpringerBriefs in optimization. $3 1566137
856 4 0 $u https://doi.org/10.1007/978-3-030-68514-0
950 $a Mathematics and Statistics (SpringerNature-11649)