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Digital
Library of the European Council for Modelling and Simulation |
Title: |
Discrete Event Optimization:
Theory, Applications And Future Challenges |
Authors: |
Andrea Matta |
Published in: |
(2016).ECMS 2016 Proceedings edited
by: Thorsen Claus, Frank Herrmann, Michael Manitz, Oliver Rose, European Council for Modeling
and Simulation. doi:10.7148/2016 ISBN:
978-0-9932440-2-5 30th
European Conference on Modelling and Simulation, Regensburg Germany, May 31st
– June 3rd, 2016 |
Citation
format: |
Andrea
Matta (2016). Discrete Event Optimization: Theory,
Applications And Future Challenges, ECMS 2016 Proceedings edited by: Thorsten
Claus, Frank Herrmann, Michael Manitz, Oliver Rose European Council for Modeling and Simulation. doi:10.7148/2016-0005 |
DOI: |
http://dx.doi.org/10.7148/2016-0005 |
Abstract: |
Optimization
of discrete event systems is often time consuming and also requires specific
approaches due to the fact that general methodologies cannot be successfully
applied to any kind of system. Conventional approaches use simulation as a
black-box oracle to estimate performance at design points generated by a
separate optimization algorithm. This decoupled approach fails to exploit an
important advantage: simulation codes are white-boxes, at least to their creators.
In fact, the full integration of the simulation model and the optimization
algorithm is possible in many situations. The
methodology Discrete Event Optimization (DEO) is presented. DEO allows the
development of integrated simulation-optimization models for queueing systems by means of the ERGLite
formalism, a subclass of ERGs (Entity Relationships
Graphs). Furthermore, DEO provides a formal way to map ERGLs
into mathematical formulations for optimization of queueing
systems. In case the obtained model is a MILP (Mixed Integer Linear
programming), DEO also provides a formal way to approximate the obtained
models based. The analytical properties of the obtained models are analyzed
in the frameworks of Sample Path Optimization and Mathematical Programming.
Several examples will be presented to show the applicability of DEO and to
point out its strengths and drawbacks. Research challenges will also be
identified. |
Full
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