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Integer Optimization by Local Search : A Domain-Independent Approach / by Joachim P. Walser.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Author/Creator:
- Walser, Joachim P., author.
- Series:
- Computer Science (Springer-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence ; 1637.
- Lecture Notes in Artificial Intelligence ; 1637
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Algorithms.
- Computer science--Mathematics.
- Computer science.
- Information technology.
- Business--Data processing.
- Business.
- Calculus of variations.
- Artificial Intelligence.
- Algorithm Analysis and Problem Complexity.
- Discrete Mathematics in Computer Science.
- IT in Business.
- Calculus of Variations and Optimal Control; Optimization.
- Local Subjects:
- Artificial Intelligence.
- Algorithm Analysis and Problem Complexity.
- Discrete Mathematics in Computer Science.
- IT in Business.
- Calculus of Variations and Optimal Control; Optimization.
- Physical Description:
- 1 online resource (XX, 144 pages).
- Edition:
- First edition 1999.
- Contained In:
- Springer eBooks
- Place of Publication:
- Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.
- System Details:
- text file PDF
- Summary:
- 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.
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-540-48369-4
- 9783540483694
- Access Restriction:
- Restricted for use by site license.
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