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Metaheuristics: Progress in Complex Systems Optimization de Karl F. Doerner

Metaheuristics: Progress in Complex Systems Optimization: Operations Research/Computer Science Interfaces Series, cartea 39

Editat de Karl F. Doerner, Michel Gendreau, Peter Greistorfer, Walter Gutjahr, Richard F. Hartl, Marc Reimann
en Limba Engleză Hardback – 23 aug 2007
The aim of Metaheuristics: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.
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.
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Specificații

ISBN-13: 9780387719191
ISBN-10: 0387719199
Pagini: 424
Ilustrații: XIV, 410 p. 66 illus.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.83 kg
Ediția:2007
Editura: Springer Us
Colecția Springer
Seria Operations Research/Computer Science Interfaces Series

Locul publicării:New York, NY, United States

Public țintă

Professional/practitioner

Cuprins

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.

Textul de pe ultima copertă

The aim of METAHEURISTICS: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.
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.

Caracteristici

All papers in the volume are carefully peer-reviewed papers, which include high-interest research papers and tutorials from top researchers A series of tutorials on developing areas in Metaheuristics are given by some of the top researchers in Metaheuristics: Edmund Burke, Reuven Rubinstein, Eric Taillard, Gilles Pesant, Pierre Hansen, and Stefan Voß This book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field Of special interest are: Fred Glover's “New Developments for Metaheuristics in Science and Industry”; “Ant Colony Optimization”; “Search-Based Software Testing”; “Cooperative Parallel Metaheuristics”; “Metaheuristics in Practice: Solving Industrial Problems in Supply Chain Management”