Overview

This text is comprised of chapters dealing with modern approaches to global optimization, including different types of heuristics. The goal of the editors is to provide a true handbook that does not focus on particular applications of the heuristics and algorithms, but rather describes the state of the art for the different methodologies. Topics covered in the handbook include various metaheuristics, such as: simulated annealing; genetic algorithms; neural networks; taboo search; shake-and-bake methods; and deformation methods. In addition, the book contains chapters on new exact stochastic and deterministic approaches to continuous and mixed-integer global optimization, such as: stochastic adaptive search; two-phase methods; branch-and-bound methods with new relaxation and branching strategies; and algorithms based on local optimization, and dynamical search. Finally, the book contains chapters on: the experimental analysis of algorithms and software; test problems; and applications.

Full Product Details

Author:   Panos M. Pardalos ,  H. Edwin Romeijn
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2002 ed.
Volume:   62
Dimensions:   Width: 15.50cm , Height: 3.10cm , Length: 23.50cm
Weight:   1.163kg
ISBN:  

9781402006326

ISBN 10:   1402006322
Pages:   572
Publication Date:   30 June 2002
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1 Tight relaxations for nonconvex optimization problems using the Reformulation-Linearization/Convexification Technique (RLT).- 2 Exact algorithms for global optimization of mixed-integer nonlinear programs.- 3 Algorithms for global optimization and discrete problems based on methods for local optimization.- 4 An introduction to dynamical search.- 5 Two-phase methods for global optimization.- 6 Simulated annealing algorithms for continuous global optimization.- 7 Stochastic Adaptive Search.- 8 Implementation of Stochastic Adaptive Search with Hit-and-Run as a generator.- 9 Genetic algorithms.- 10 Dataflow learning in coupled lattices: an application to artificial neural networks.- 11 Taboo Search: an approach to the multiple-minima problem for continuous functions.- 12 Recent advances in the direct methods of X-ray crystallography.- 13 Deformation methods of global optimization in chemistry and physics.- 14 Experimental analysis of algorithms.- 15 Global optimization: software, test problems, and applications.

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