Discrete Diversity and Dispersion Maximization A Tutorial on Metaheuristic Optimization /
This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. Maximum diversity problems arise in many practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimiza...
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| Drugi avtorji: | , |
| Format: | Elektronski eKnjiga |
| Jezik: | angleščina |
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Springer International Publishing : Imprint: Springer,
2023.
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| Izdaja: | 1st ed. 2023. |
| Serija: | Springer Optimization and Its Applications,
204 |
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| Online dostop: | https://doi.org/10.1007/978-3-031-38310-6 |
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Kazalo:
- Part I Models: Discrete diversity optimization. Models and instances (Martınez-Gavara)
- The Origins of Discrete Diversity (Kuby)
- Geometrical Analysis of Solutions (Alcaraz)
- Part II Constructive based Metaheuristics: Constructive and destructive methods in heuristic search (Aringhieri)
- Greedy Randomized Adaptive Search Procedure (Sánchez-Oro)
- Iterated Greedy (Lozano)
- Part III Trajectory based Metaheuristics: Tabu Search (Martínez-Gavara)
- Variable neighborhood search (Urošević)
- Less is More approach (Todosijević)
- Simulated Annealing (Kincaid)
- Part IV Population based Metaheuristics: Scatter Search (Martınez-Gavara)
- Memetic Algorithms (Hao)
- Part V Extensions: Data Mining in Heuristic Search (Martins)
- Multi-objective Optimization (Colmenar).