Buch, Englisch, 157 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 2759 g
Reihe: Artificial Intelligence: Foundations, Theory, and Algorithms
Powerful Tools for Optimization
Buch, Englisch, 157 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 2759 g
Reihe: Artificial Intelligence: Foundations, Theory, and Algorithms
ISBN: 978-3-319-80907-6
Verlag: Springer International Publishing
The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
Weitere Infos & Material
Introduction.- Incomplete Solution Representations and Decoders.- Hybridization Based on Problem Instance Reduction.- Hybridization Based on Large Neighborhood Search.- Making Use of a Parallel, Non-independent, Construction of Solutions Within Metaheuristics.- Hybridization Based on Complete Solution Archives.- Further Hybrids and Conclusions.