Integer Optimization by Local Search

Joachim P. Walser

ISBN 10: 3540663673 / ISBN 13: 9783540663676

Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 1999, 1999

Beschreibung

Neuware -Integer Optimization addresses a wide spectrum of practically important optimization problems and represents a major challenge for algorithmics. The goal of integer optimization is to solve a system of constraints and optimization criteria over discrete variables.Integer Optimization by Local Search introduces a new approach to domain-independent integer optimization, which, unlike traditional strategies, is based on local search. It develops the central concepts and strategies of integer local search and describes possible combinations with classical methods from linear programming. The surprising effectiveness of the approach is demonstrated in a variety of case studies on large-scale, realistic problems, including production planning, timetabling, radar surveillance, and sports scheduling. The monograph is written for practitioners and researchers from artificial intelligence and operations research.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 164 pp. Englisch.

Bestandsnummer des Verkäufers 9783540663676

Bibliografische Details

• Titel: Integer Optimization by Local Search
• Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Aug 1999
• Erscheinungsjahr: 1999
• Sprache: Englisch
• ISBN-10: 3540663673
• ISBN-13: 9783540663676
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

Integer Optimization addresses a wide spectrum of practically important optimization problems and represents a major challenge for algorithmics. The goal of integer optimization is to solve a system of constraints and optimization criteria over discrete variables.
Integer Optimization by Local Search introduces a new approach to domain-independent integer optimization, which, unlike traditional strategies, is based on local search. It develops the central concepts and strategies of integer local search and describes possible combinations with classical methods from linear programming. The surprising effectiveness of the approach is demonstrated in a variety of case studies on large-scale, realistic problems, including production planning, timetabling, radar surveillance, and sports scheduling. The monograph is written for practitioners and researchers from artificial intelligence and operations research.