A multi-level approach to planning and scheduling resources for aviation training

Johnstone, Michael, Le, Vu, Novak, Ana, Khan, Burhan, Creighton, Douglas, Tracey, Luke and Nguyen, Vivian 2015, A multi-level approach to planning and scheduling resources for aviation training, in MODSIM2015: Partnering with industry and the community for innovation and impact through modelling. Proceedings of the 21st International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia and New Zealand, Canberra, A.C.T., pp. 1848-1854.

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Title A multi-level approach to planning and scheduling resources for aviation training
Author(s) Johnstone, MichaelORCID iD for Johnstone, Michael orcid.org/0000-0002-3005-8911
Le, VuORCID iD for Le, Vu orcid.org/0000-0003-0648-6112
Novak, Ana
Khan, Burhan
Creighton, DouglasORCID iD for Creighton, Douglas orcid.org/0000-0002-9217-1231
Tracey, Luke
Nguyen, Vivian
Conference name International Congress on Modelling and Simulation (21st: 2015: Gold Coast, Qld.)
Conference location Gold Coast, Qld.
Conference dates 29 Nov - 4 Dec. 2015
Title of proceedings MODSIM2015: Partnering with industry and the community for innovation and impact through modelling. Proceedings of the 21st International Congress on Modelling and Simulation
Publication date 2015
Start page 1848
End page 1854
Total pages 7
Publisher Modelling and Simulation Society of Australia and New Zealand
Place of publication Canberra, A.C.T.
Keyword(s) System dynamics
Discrete event simulation
Training continuum
Summary This paper describes a multi-level system dynamics (SD) / discrete event simulation (DES) approach for assessing planning and scheduling problems within an aviation training continuum. The aviation training continuum is a complex system, consisting of multiple aviation schools interacting through interschool student and instructor flows that are affected by external triggers such as resource availability and the weather.
SD was used to model the overall training continuum at a macro level to ascertain relationships between system entities. SD also assisted in developing a shared understanding of the training continuum, which involves constructing the definitions of the training requirements, resources and policy objectives. An end-to-end model of the continuum is easy to relate to, while dynamic visualisation of system behaviour provides a method for exploration of the model.
DES was used for micro level exploration of an individual school within the training continuum to capture the physical aspects of the system including resource capacity requirements, bottlenecks and student waiting times. It was also used to model stochastic events such as weather and student availability. DES has the advantage of being able to represent system variability and accurately reflect the limitations imposed on a system by resource constraints.
Through sharing results between the models, we demonstrate a multi-level approach to the analysis of the overall continuum. The SD model provides the school’s targeted demand to the DES model. The detailed DES model is able to assess schedules in the presence of resource constraints and variability and provide the expected capacity of a school to the high level SD model, subjected to constraints such as instructor availability or budgeted number of training systems. The SD model allows stakeholders to assess how policy and planning affect the continuum, both in the short and the long term.
The development of this approach permits moving the analysis of the continuum between SD and DES models as appropriate for given system entities, scales and tasks. The resultant model outcomes are propagated between the continuum and the detailed DES model, iteratively generating an assessment of the entire set of plans and schedule across the continuum. Combining data and information between SD and DES models and techniques assures relevance to the stakeholder needs and effective problem scoping and scaling that can also evolve with dynamic architecture and policy requirements.
An example case study shows the combined use of the two models and how they are used to evaluate a typical scenario where increased demand is placed on the training continuum. The multi-level approach provides a high level indication of training requirements to the model of the new training school, where the detailed model indicates the resources required to achieve those particular student levels.
Language eng
Field of Research 080110 Simulation and Modelling
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, MSSANZ
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082978

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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