Overview
- 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
Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)
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Table of contents (7 chapters)
Keywords
- optimization algorithms
- inventory routing
- lot sizing
- facility location
- combinatorics
- metaheuristics
- open problems
- efficient algorithm portfolios
- trading-based budget allocation
- market-based algorithms
- Circulant weighing matrices
- sequential models
- parallel models
- algorithm portfolios
- constituent algorithms
- metaheuristic optimization algorithms
About this book
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, andopen problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.
Authors and Affiliations
Bibliographic Information
Book Title: Algorithm Portfolios
Book Subtitle: Advances, Applications, and Challenges
Authors: Dimitris Souravlias, Konstantinos E. Parsopoulos, Ilias S. Kotsireas, Panos M. Pardalos
Series Title: SpringerBriefs in Optimization
DOI: https://doi.org/10.1007/978-3-030-68514-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-68513-3Published: 25 March 2021
eBook ISBN: 978-3-030-68514-0Published: 24 March 2021
Series ISSN: 2190-8354
Series E-ISSN: 2191-575X
Edition Number: 1
Number of Pages: XIV, 92
Number of Illustrations: 5 b/w illustrations
Topics: Operations Research, Management Science, Algorithms, Control Structures and Microprogramming, Discrete Mathematics