Article

Solving an avionics real-time scheduling problem by advanced IP-methods

Authors:

Friedrich Eisenbrand,

Karthikeyan Kesavan,

Raju S. Mattikalli,

Martin Niemeier,

Arnold W. Nordsieck,

Martin Skutella,

José Verschae,

Andreas WieseAuthors Info & Claims

ESA'10: Proceedings of the 18th annual European conference on Algorithms: Part I

Pages 11 - 22

Published: 06 September 2010 Publication History

Abstract

We report on the solution of a real-time scheduling problem that arises in the design of software-based operation control of aircraft. A set of tasks has to be distributed on a minimum number of machines and offsets of the tasks have to be computed. The tasks emit jobs periodically starting at their offset and then need to be executed on the machines without any delay. Also, further constraints in terms of memory usage and redundancy requirements have to be met. Approaches based on standard integer programming formulations fail to solve our real-world instances. By exploiting structural insights of the problem we obtain an IP-formulation and primal heuristics that together solve the real-world instances to optimality and outperform text-book approaches by several orders of magnitude. Our methods lead, for the first time, to an industry strength tool to optimally schedule aircraft sized problems.

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Cited By

Pira CArtigues C(2013)An Efficient Best Response Heuristic for a Non-preemptive Strictly Periodic Scheduling ProblemRevised Selected Papers of the 7th International Conference on Learning and Intelligent Optimization - Volume 799710.1007/978-3-642-44973-4_30(281-287)Online publication date: 7-Jan-2013
https://dl.acm.org/doi/10.1007/978-3-642-44973-4_30

Solving an avionics real-time scheduling problem by advanced IP-methods
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
    2. Online algorithms
      1. Online learning algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning

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Information & Contributors

Information

Published In

cover image Guide Proceedings

ESA'10: Proceedings of the 18th annual European conference on Algorithms: Part I

September 2010

587 pages

ISBN:3642157742

Editors:
Mark de Berg
Department of Mathematics and Computing Science, TU Eindhoven, Eindhoven, The Netherlands
,
Ulrich Meyer
Institute for Computer Science, Goethe University, Frankfurt/Main, Germany

Sponsors

Springer
London Mathematical Society
University of Liverpool
EATCS: European Association for Theoretical Computer Science
International Society of Computational Geometry

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 06 September 2010

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Cited By

Pira CArtigues C(2013)An Efficient Best Response Heuristic for a Non-preemptive Strictly Periodic Scheduling ProblemRevised Selected Papers of the 7th International Conference on Learning and Intelligent Optimization - Volume 799710.1007/978-3-642-44973-4_30(281-287)Online publication date: 7-Jan-2013
https://dl.acm.org/doi/10.1007/978-3-642-44973-4_30

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