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A constraint generation procedure for pre-runtime scheduling of integrated modular avionic systems
Saab AB, Sweden.
Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.
Saab AB, Sweden.
Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-2081-2888
2017 (English)In: Proceedings of the 13th Workshop on Models and Algorithms for Planning and Scheduling Problems / [ed] Susanne Albers, Nicole Megow, Andreas S. Schulz, Leen Stougie, 2017Conference paper, Oral presentation with published abstract (Other academic)
Abstract [en]

In modern integrated modular avionic systems, applications share hardware resources on a common avionic platform. Such an architecture necessitates strict requirements on the spatial and temporal partitioning of the system to prevent fault propagation between different aircraft functions. One way to establish a temporal partitioning is through pre-runtime scheduling of the system, which involves creating a schedule for both tasks and a communication network.

While the avionic systems are growing more and more complex, so is the challenge of scheduling them. Scheduling of the system has an important role in the development of new avionic systems since functionality typically is added to the system over a period of several years and a scheduling tool is used both to detect if the platform can host the new functionality and, in case this is possible, to create a new schedule. For this reason an exact solution strategy for avionics scheduling is preferred over a heuristic one.

In this paper we present a mathematical model for an industrially relevant avionic system and present a constraint generation  procedure for scheduling of such systems. We apply our optimisation approach to instances provided by our industrial partner. These instances are of relevance for the development of future avionic systems and contain up to 20 000 tasks to be scheduled. The computational results show that our optimisation approach can be used to create schedules for such instances within reasonable time.

Place, publisher, year, edition, pages
2017.
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-138431OAI: oai:DiVA.org:liu-138431DiVA, id: diva2:1110471
Conference
MAPSP 2017, The 13th Workshop on Models and Algorithms for Planning and Scheduling Problems
Available from: 2017-06-15 Created: 2017-06-15 Last updated: 2017-07-06

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf