Overview

In 1995 the Handbook of Global Optimization (first volume), edited by R. Horst, and P.M. Pardalos, was published. This second volume of the Handbook of Global Optimization is comprised of chapters dealing with modern approaches to global optimization, including different types of heuristics. 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, algorithms based on local optimization, and dynamical search. Finally, the book contains chapters on 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:   Softcover reprint of the original 1st ed. 2002
Volume:   62
Dimensions:   Width: 15.50cm , Height: 3.00cm , Length: 23.50cm
Weight:   0.884kg
ISBN:  

9781441952219

ISBN 10:   1441952217
Pages:   572
Publication Date:   29 September 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock  
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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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