Algorithm Portfolios: Advances, Applications, and Challenges: SpringerBriefs in Optimization
Autor Dimitris Souravlias, Konstantinos E. Parsopoulos, Ilias S. Kotsireas, Panos M. Pardalosen Limba Engleză Paperback – 25 mar 2021
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Specificații
ISBN-13: 9783030685133
ISBN-10: 3030685136
Pagini: 92
Ilustrații: XIV, 92 p. 5 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.45 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Optimization
Locul publicării:Cham, Switzerland
ISBN-10: 3030685136
Pagini: 92
Ilustrații: XIV, 92 p. 5 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.45 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Optimization
Locul publicării:Cham, Switzerland
Cuprins
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.
Textul de pe ultima copertă
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.
Caracteristici
Primary reference point for researchers and doctoral students seeking a quick guide Provides essential insights about choices of algorithms and configurations to tackle optimization problems Explores future directions, new challenges, and open problems