Metaheuristics:: Progress as Real Problem Solvers

ISBN-13: 9780387253824 / Angielski / Twarda / 2005 / 414 str.

Toshihide Ibaraki; Koji Nonobe; Mutsunori Yagiura

Opis

Our globalized world brings us increasing complexity and many computationally hard problems. Metaheuristics are mathematical optimization methods that have become a powerful answer to many of these difficult problems. As a growing set of robust methods, Metaheuristics is producing effective algorithms that compute approximate solutions of high quality in realistic computational time. 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. The volume's objective is to consolidate works in operations research, management science, artificial intelligence, computer science, and related fields to further the understanding of basic principles and the developing domain of Metaheuristics. This includes 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.

Spis treści

Preface.- Metaheuristic Agent Processes (MAPs).- GRASP with Path-Relinking: Recent advances and applications.- 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: An application for the paper industry.- 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.- 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 Neighborhood in a Tabu Search.- Constraint Oriented Neighborhoods - A New Search Strategy in Metaheuristics.