Matheuristics: Algorithms and Implementations: EURO Advanced Tutorials on Operational Research
Autor Vittorio Maniezzo, Marco Antonio Boschetti, Thomas Stützleen Limba Engleză Paperback – 30 apr 2022
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Specificații
ISBN-13: 9783030702793
ISBN-10: 3030702790
Pagini: 214
Ilustrații: XVIII, 214 p. 41 illus., 22 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.33 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria EURO Advanced Tutorials on Operational Research
Locul publicării:Cham, Switzerland
ISBN-10: 3030702790
Pagini: 214
Ilustrații: XVIII, 214 p. 41 illus., 22 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.33 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria EURO Advanced Tutorials on Operational Research
Locul publicării:Cham, Switzerland
Cuprins
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.
Notă biografică
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.
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.
Textul de pe ultima copertă
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.
Caracteristici
Includes over 40 algorithms with associated codes and step-by-step trace of sample runs Provides detailed presentation of best-known metaheuristics and their mathematical hybrids Describes both extensions of well-known heuristics and of innovative, matheuristic-only approaches