Buch, Englisch, Band 39, 410 Seiten, HC runder Rücken kaschiert, Format (B × H): 132 mm x 209 mm, Gewicht: 546 g
Reihe: Operations Research/Computer Science Interfaces Series
Progress in Complex Systems Optimization
Buch, Englisch, Band 39, 410 Seiten, HC runder Rücken kaschiert, Format (B × H): 132 mm x 209 mm, Gewicht: 546 g
Reihe: Operations Research/Computer Science Interfaces Series
ISBN: 978-0-387-71919-1
Verlag: Springer US
Highlighted are recent developments in the areas of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable Neighborhood Search, Hyper-heuristics, Constraint Programming, Iterated Local Search, GRASP, bio-inspired algorithms like Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization or Swarm Intelligence, and several other paradigms.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Mathematik | Informatik EDV | Informatik Technische Informatik Systemverwaltung & Management
- Mathematik | Informatik Mathematik Operations Research Spieltheorie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
Weitere Infos & Material
Scatter Search.- Experiments Using Scatter Search for the Multidemand Multidimensional Knapsack Problem.- A Scatter Search Heuristic for the Fixed-Charge Capacitated Network Design Problem.- Tabu Search.- Tabu Search-Based Metaheuristic Algorithm for Large-scale Set Covering Problems.- Log-Truck Scheduling with a Tabu Search Strategy.- Nature-inspired methods.- Solving the Capacitated Multi-Facility Weber Problem by Simulated Annealing, Threshold Accepting and Genetic Algorithms.- Reviewer Assignment for Scientific Articles using Memetic Algorithms.- GRASP and Iterative Methods.- Grasp with Path-Relinking for the Tsp.- Using a Randomised Iterative Improvement Algorithm with Composite Neighbourhood Structures for the University Course Timetabling Problem.- Dynamic and Stochastic Problems.- Variable Neighborhood Search for the Probabilistic Satisfiability Problem.- The ACO/F-Race Algorithm for Combinatorial Optimization Under Uncertainty.- Adaptive Control of Genetic Parameters for Dynamic Combinatorial Problems.- A Memetic Algorithm for Dynamic Location Problems.- A Study of Canonical GAs for NSOPs.- Particle Swarm Optimization and Sequential Sampling in Noisy Environments.- Distributed and Parallel Algorithms.- Embedding a Chained Lin-Kernighan Algorithm into a Distributed Algorithm.- Exploring Grid Implementations of Parallel Cooperative Metaheuristics.- Algorithm Tuning, Algorithm Design and Software Tools.- Using Experimental Design to Analyze Stochastic Local Search Algorithms for Multiobjective Problems.- Distance Measures and Fitness-Distance Analysis for the Capacitated Vehicle Routing Problem.- Tuning Tabu Search Strategies Via Visual Diagnosis.- Solving Vehicle Routing Using IOPT.