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Integer Optimization by Local Search [electronic resource] : A Domain-Independent Approach /

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 1637Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999Edition: 1st ed. 1999Description: XX, 144 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540483694
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
Frameworks for Combinatorial Optimization -- Local Search for Integer Constraints -- Case Studies Methodology -- Time-Tabling and Sports Scheduling -- Covering and Assignment -- Capacitated Production Planning -- Extensions.
In: Springer Nature eBookSummary: 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.
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Frameworks for Combinatorial Optimization -- Local Search for Integer Constraints -- Case Studies Methodology -- Time-Tabling and Sports Scheduling -- Covering and Assignment -- Capacitated Production Planning -- Extensions.

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.

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