Logic-Based Methods for Optimization

Combining Optimization and Constraint Satisfaction
REV and Thumb I Auflage
ISBN: 978-0-471-38521-9
Verlag: Wiley

Buch, Englisch, 520 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 941 g

Reihe: Wiley-Interscience Series in Discrete Mathematics and Optimization

Dieser Band untersucht die Rolle der Logik bei der Optimierung - Grundlage für eine neue Generation von Vorlesungen in diskreter Optimierung! In ausgesprochen klarem, technisch sauberen Stil werden Tools und Techniken erläutert sowie vielfältige Programmieroptionen (ILOG, CPLEX, OPL, AMPL, GAMS und andere). Mit zahlreichen anschaulichen Beispielen. (07/00)

Autoren/Hrsg.

Hooker, John

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik Mathematik Operations Research

Inhaltsverzeichnis

Some Examples.

The Logic of Propositions.

The Logic of Discrete Variables.

The Logic of 0-1 Inequalities.

Cardinality Clauses.

Classical Boolean Methods.

Logic-Based Modeling.

Logic-Based Branch and Bound.

Constraint Generation.

Domain Reduction.

Constraint Programming.

Continuous Relaxations.

Decomposition Methods.

Branching Rules.

Relaxation Duality.

Inference Duality.

Search Strategies.

Logic-Based Benders Decomposition.

Nonserial Dynamic Programming.

Discrete Relaxations.

References.

Index.

Über Autor(innen)

JOHN HOOKER, PhD, is Professor of Operations Research and T. Jerome Holleran Professor of Business Ethics and Social Responsibility at the Graduate School of Industrial Administration, Carnegie Mellon University. Well-known for his work in the operations research/computer science interface, Dr. Hooker has published over 80 articles and coauthored (with Vijay Chandru) Optimization Methods for Logical Inference, also available from Wiley.