Feasibility and Infeasibility in Optimization:: Algorithms and Computational Methods (International Series in Operations Research & Management Science)

Chinneck, John W.

ISBN 10: 0387749314 / ISBN 13: 9780387749310

Edité par Springer, 2007

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N° de réf. du vendeur ERICA70403877493145

Détails bibliographiques

• Titre: Feasibility and Infeasibility in Optimization:: Algorithms and Computational Methods (International Series in Operations Research & Management Science)
• Éditeur: Springer
• Date de parution: 2007
• Langue: anglais
• ISBN à 10 chiffres: 0387749314
• ISBN à 13 chiffres: 9780387749310
• Reliure: Hardcover
• État de l'article: Like New
• Type de livre: book

A propos de ce titre

Synopsis

Feasibility and Infeasibility in Optimization is an expository book focused on practical algorithms related to feasibility and infeasibility in optimization. Part I addresses algorithms for seeking feasibility quickly, including recent algorithms for the difficult cases of nonlinear and mixed-integer programs. Part II provides algorithms for analyzing infeasibility by isolating minimal infeasible (or maximum feasible) subsets of constraints, or by finding the best repair for the infeasibility. Part III describes surprising applications in areas such as classification, computational biology, and medicine. Connections to constraint programming are shown. A main goal is to impart an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. The book is of interest to researchers, students, and practitioners across the applied sciences who are working on optimization problems.

Présentation de l'éditeur

Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.