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Metaheuristics:: Progress as Real Problem Solvers: Operations Research/Computer Science Interfaces Series, cartea 32

Editat de Toshihide Ibaraki, Koji Nonobe, Mutsunori Yagiura
en Limba Engleză Paperback – 8 dec 2010
Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field. Included are an invited paper by F. Glover and G. Kochenberger, which discusses the concept of Metaheuristic agent processes, and a tutorial paper by M.G.C. Resende and C.C. Ribeiro discussing GRASP with path-relinking. Other papers discuss problem-solving approaches to timetabling, automated planograms, elevators, space allocation, shift design, cutting stock, flexible shop scheduling, colorectal cancer and cartography. A final group of methodology papers clarify various aspects of Metaheuristics from the computational view point.
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Specificații

ISBN-13: 9781441937902
ISBN-10: 1441937900
Pagini: 428
Ilustrații: XII, 414 p. 106 illus.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.59 kg
Ediția:Softcover reprint of hardcover 1st ed. 2005
Editura: Springer Us
Colecția Springer
Seria Operations Research/Computer Science Interfaces Series

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

Invited Paper.- Metaheuristic Agent Processes (MAPS).- Tutorial Paper.- GRASP with Path-Relinking: Recent Advances and Applications.- Papers on Problem Solving.- A Tabu Search Heuristic for a University Timetabling Problem.- An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-Heuristic.- Validation and Optimization of an Elevator Simulation Model with Modern Search Heuristics.- Multi-Objective Hyper-Heuristic Approaches for Space Allocation and Timetabling.- Theory and Practice of the Minimum Shift Design Problem.- Local Search Algorithms for the Two-Dimensional Cutting Stock Problem with a Given Number of Different Patterns.- A Generic Object-Oriented Tabu Search Framework.- Bi-Objective Sequencing of Cutting Patterns.- Metaheuristics Approach for Rule Acquisition in Flexible Shop Scheduling Problems.- Predicting Colorectal Cancer Recurrence: A Hybrid Neural Networks-Based Approach.- A Constructive Genetic Approach to Point-Feature Cartographic Label Placement.- Papers on Methodologies.- Parallel Strategies for Grasp with Path-Relinking.- Speeding Up Local Search Neighborhood Evaluation for A Multi-Dimensional Knapsack Problem.- Computationally Difficult Instances for the Uncapacitated Facility Location Problem.- Consistent Neighbourhood in a Tabu Search.- Constraint Oriented Neighbourhoods — A New Search Strategy in Metaheuristics.

Caracteristici

Surveys some of the most recent solution approaches involving genetic algorithms, simulated annealing, tabu search, evolutionary computation, greedy randomized adaptive search procedures (GRASP), scatter search, ant system, variable neighborhood search, guided local search, iterated local search, noising methods, threshold accepting, memetic algorithms, neural networks, and other hybrid and/or variant approaches for solving hard combinatorial problems