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Algorithm Portfolios : Advances, Applications, and Challenges / by Dimitris Souravlias, Konstantinos E. Parsopoulos, Ilias S. Kotsireas, Panos M. Pardalos.
Springer Nature - Springer Mathematics and Statistics eBooks 2021 English International Available online
View online- Format:
- Book
- Author/Creator:
- Souravlias, Dimitris, author.
- Series:
- SpringerBriefs in Optimization, 2191-575X
- Language:
- English
- Subjects (All):
- Operations research.
- Management science.
- Algorithms.
- Microprogramming.
- Discrete mathematics.
- Operations Research, Management Science.
- Control Structures and Microprogramming.
- Discrete Mathematics.
- Local Subjects:
- Operations Research, Management Science.
- Algorithms.
- Control Structures and Microprogramming.
- Discrete Mathematics.
- Physical Description:
- 1 online resource (xiv, 92 pages) : illustrations.
- Edition:
- 1st ed. 2021.
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- Summary:
- 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.
- Contents:
- 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.
- Notes:
- Includes bibliographical references.
- ISBN:
- 3-030-68514-4
- OCLC:
- 1243349954
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