Matheuristics

Algorithms and Implementations
1. Auflage 2021
ISBN: 978-3-030-70279-3
Verlag: Springer International Publishing

Buch, Englisch, 214 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 359 g

Reihe: EURO Advanced Tutorials on Operational Research

This book is the first comprehensive tutorial on matheuristics. Matheuristics are based on mathematical extensions of previously known heuristics, mainly metaheuristics, and on original, area-specific approaches. This tutorial provides a detailed discussion of both contributions, presenting the pseudocodes of over 40 algorithms, abundant literature references, and for each case a step-by-step description of a sample run on a common Generalized Assignment Problem example. C++ source codes of all algorithms are available in an associated SW repository.

Zielgruppe

Graduate

Autoren/Hrsg.

Maniezzo, Vittorio

Stützle, Thomas

Boschetti, Marco Antonio

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik Mathematik Operations Research
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung

Inhaltsverzeichnis

Part I: Contextual Issues.- 1. The Generalized Assignment Problem.- 2. Automatic Design for Matheuristics.- Part II: Metaheuristic Hybrids.- 3. Single Solution Metaheuristics.- 4. Population-Based metaheuristics.- Part III: Original Matheuristics.- 5. Diving Heuristics.- 6. Very Large-Scale Neighborhood Search.- 7. Decomposition Based Heuristics.- 8. Corridor Method.- 9. Kernel Search.- 10. Fore-and-Back.

Über Autor(innen)

Vittorio Maniezzo is a Full Professor of Computer Science at the University of Bologna, Italy. He has been working on heuristic algorithms for combinatorial optimization for decades, first contributing to the original design of ant system optimization, and then establishing the area of matheuristics. His research interests include operational analytics, combining matheuristics with predictive modules.

Marco Antonio Boschetti is an Associate Professor at the Department of Mathematics, University of Bologna, Italy. He holds an Msc in Computer Science from the University of Bologna and a PhD in Operational Research from the Management School, Imperial College, London, UK. His main research and consulting interests include quantitative methods for management science. In particular, he works on exact and heuristic solution methods based on mathematical programming and combinatorial optimization approaches.

Thomas Stützle is a Research Director at the Belgian F.R.S.-FNRS, working at the IRIDIA laboratory of Universitélibre de Bruxelles (ULB), Belgium. He is the co-author of two books, Stochastic Local Search: Foundations and Applications and Ant Colony Optimization, both of which are the main reference sources in their respective areas. His research interests include metaheuristics and stochastic local search, swarm intelligence, methodologies for engineering stochastic local search algorithms, multi-objective optimization and the automatic configuration of algorithms.