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Springer Global Optimization - Computational Methods Book

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Description

Explore the complexities of global optimization with this Springer publication. This volume addresses the challenges of computing the global optimum for multivariable functions across science, engineering, and technology. Since many optimization problems belong to the NP-hard complexity class, traditional descent algorithms based on local information are often insufficient for finding solutions. This text examines methods for handling variables that can be continuous or discrete, even when they must satisfy specific constraints. It provides a deep look at computational methods and applications designed to tackle these difficult problems where local information alone cannot provide the necessary results.

Key Features

This Springer book covers computational methods and applications for global optimization problems.

It addresses multivariable functions where variables can be either continuous or discrete.

The text provides solutions for optimization problems that must satisfy specific constraints.

It explores methods for solving NP-hard problems that are difficult for traditional descent algorithms.

This volume is part of the Nonconvex Optimization and Its Applications series, volume 7.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
29 February 1996
Listed Since
15 December 2006

Barcode

No barcode data available

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