[Zurück]

S. Emrich, D. Wiegand, F. Breitenecker, M. Sreckovic, A. Kovacs, S. Tauböck, M. Bruckner, B. Rozsenich, S. Alkilani, N. Popper:
"Efficient Use of Space Over Time - Deployment of the MoreSpace-Tool";
Vortrag: MATHMOD 2012 - 7th Vienna Conference on Mathematical Modelling, Wien; 14.02.2012 - 17.02.2012; in: "Preprints Mathmod 2012 Vienna - Full Paper Volume", F. Breitenecker, I. Troch (Hrg.); Argesim / Asim, 38 (2012), S. 359 - 360.

Motivational Idea. The debate around global warming and necessary consequences is still far from being settled;
nevertheless it has become clear that the ecological footprint has to be reduced drastically. Massive investments
in new technology can only be a part of this effort. The question arises what to do with existing buildings, as it is
unrealistic to rebuild (all of) them with state of the art-technology.
A simple but elegant solution for this is to increase utilization-efficiency. This directly leads to a better footprint/
utilization ratio and also features positive economic side-effects (e.g. reduced "costs per unit" or savings of resources).
As proposed in a study carried out at the ETH Zürich [1] educational facilities hold a high potential yield
with respect to such improvements.
State of the Art. Extensive literature search shows that the problem of university course timetabling is still
not solved satisfactory (at large scale). Various attempts and algorithms for scheduling and timetabling exist,
although there are only very few course timetabling papers that actually report that the (research) methods have
been implemented and are used in an institution. Methods for the simulation of room utilization are - to the authors´
knowledge - not in use at all.
Approach. Within the research project "MoreSpace" such a model for simulation of room utilization (primarily
of university buildings) is being developed. It is based on discrete event simulation, cellular automata, agent-based
techniques and business process modeling (see [2, 3] for further reference). In order to successfully deploy this
model within the intended peripheral real-life system, its preconditions and requirements have to be met. Thus an
analysis - and eventually a transformation - of that peripheral system is necessary for the successful introduction
of the simulation model. While still in progress, this analysis and its findings are covered within the paper.
At first three possible modes of operation (of the model) are identified. Next the model´s preconditions are derived
and split into structural preconditions and necessary input-data. For the latter an entity relationship model
(ERM) is developed which describes the model´s database. The ERM is then mapped onto the peripheral system,
which requires an assessment of disposable data-sources and their (quantitative and qualitative) content. This subsequently
leads to the necessity of a stakeholder analysis, investigating their interconnecting relationships. Based
on the stakeholder analysis the processes surrounding the space management (e.g. room reservation) are explored
and described with business process models (BPM).
Further a deployment matrix is set up, which puts the mode of operation into context with met preconditions and
required depth of system-integration. Thus is becomes possible to estimate whether a model can be deployed as
intended or not; with alternatives being either a transformation of the system, reformulation of the question(s)
towards the model or - in the worst case - abortion of the deployment process.
Outlook. As with all simulation results the data needs post-processing which requires data mining and visualization
techniques to draw sensible conclusions. Since stakeholders´ interests differ so do their perspectives
upon simulation outcome. Subsequently post-processing and visualization need "individual" fitting to meet those
demands. For this an automated but customizable visualization-tool is currently under development.
The methods applied for system analysis seem fairly adequate to prepare the model deployment within a real-life
system. Motivated by the positive insights gained, further investigation on utilization of techniques for efficient
model deployment (also in other areas of simulation) seems rewarding.