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A matheuristic approach to large-scale avionic scheduling
Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering. Saab AB, SE-581 88 Linköping.ORCID iD: 0000-0002-9498-1924
Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering. Saab AB, SE-581 88 Linköping.
Saab AB, SE-581 88 Linköping.
Saab AB, SE-581 88 Linköping.
2019 (English)Report (Other academic)
Abstract [en]

Pre-runtime scheduling of avionic systems is used to ensure that the systems provide the desired functionality at the correct time. This paper considers scheduling of an integrated modular avionic system which from a more general perspective can be seen as a multiprocessor scheduling problem that includes a communication network. The addressed system is practically relevant and the computational evaluations are made on large-scale instances developed together with the industrial partner Saab. A subset of the instances is made publicly available.

Our contribution is a matheuristic for solving these large-scale instances and it is obtained by improving the model formulations used in a previously suggested constraint generation procedure and by including an adaptive large neighbourhood search to extend it into a matheuristic. Characteristics of our adaptive large neighbourhood search are that it is made over both discrete and continuous variables and that it needs to balance the search for feasibility and profitable objective value. The repair operation is to apply a mixed-integer programming solver on a model where most of the constraints are treated as soft and a violation of them is instead penalised in the objective function. The largest solved instance, with respect to the number of tasks, has 45 988 tasks and 2 011 communication messages.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. , p. 40
Series
LiTH-MAT-R, ISSN 0348-2960 ; 2019:2
Keywords [en]
Multiprocessor scheduling; avionic system; matheuristic; adaptive large neighbourhood search; integer programming; scheduling
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-157140ISRN: LiTH-MAT-R--2019/02--SEOAI: oai:DiVA.org:liu-157140DiVA, id: diva2:1318929
Available from: 2019-05-29 Created: 2019-05-29 Last updated: 2019-05-29
In thesis
1. Optimisation-based scheduling of an avionic system
Open this publication in new window or tab >>Optimisation-based scheduling of an avionic system
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Modern computer systems in aircraft are often based on an integrated modular avionic architecture. In this architecture, software applications share hardware resources on a common avionic platform. Many functions in an aircraft are controlled by software and a failure in such software can have severe consequences. In order to avoid malfunction, there are many aspects to consider. One aspect is to ensure that the activities in the system is done at the right time with the right resources. To analyse if this is possible or not is often called schedulability analysis.

When multiple functions are using the same resources, the schedulability analysis becomes increasingly challenging. This thesis focuses on a pre-runtime scheduling problem of an integrated modular avionic system proposed by our industrial partner Saab. The purpose of this problem is to find a feasible schedule or prove that none exists as part of a schedulability analysis.

For the system that we study, there are two major challenges. One is that task and communication scheduling are integrated and the other is that there is a large amount of tasks to schedule. For the largest instances, there are more than 10 000 tasks on a single module. In order to solve such problems, we have developed a matheuristic. At the core of this matheuristic is a constraint generation procedure designed to handle the challenges of the scheduling problem.

The constraint generation procedure is based on first making a relaxed scheduling decision and then evaluating this in a separate problem where a complete schedule is produced. This yields a decomposition where most technical details are considered in the relaxed problem, and the actual scheduling of tasks is handled in a subproblem. Both the relaxed problem and the subproblem are formulated and solved as mixed integer programs.

The heuristic component of the matheuristic is that the relaxed problem is solved using an adaptive large neighbourhood search method. Instead of solving the relaxed problem as a single mixed integer program, the adaptive large neighbourhood search explores neighbourhoods through solving a series of mixed integer programs. Features of this search method are that it is made over both discrete and continuous variables and it needs to balance feasibility against profitable objective value.

The matheuristic described in this thesis has been implemented in a scheduling tool. This scheduling tool has been applied to instances provided by our industrial partner and to a set of public instances that we have developed. With this tool, we have solved instances with more than 45 000 tasks.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 38
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1844
National Category
Mathematics
Identifiers
urn:nbn:se:liu:diva-156695 (URN)10.3384/lic.diva-156695 (DOI)9789176850565 (ISBN)
Presentation
2019-06-13, Nobel BL32, B Building, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2019-05-24 Created: 2019-05-09 Last updated: 2019-05-29Bibliographically approved

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Karlsson, EmilRönnberg, Elina

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