all pictures ŠTH Wildau, taken by Matthias Friel
all pictures: ŠTH Wildau, taken by Matthias Friel
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Complex systems in economic, engineering and
natural sciences involve the solving of many optimisation problems.
Many of the present approaches consider operations research
optimisation models. Analytically tractable models are impractical
in change settings due to their limitations in modelling important
details and features of real world complex systems. Simulation
models, on the other hand, provide the flexibility to accommodate
arbitrary stochastic elements, and generally allow modelling of all
the complexities and dynamics of real world applications without
undue simplifying assumptions. However, simulation itself is not an
optimisation approach. Thus, in this track methods and approaches of
simulation and of the solution of optimisation problems shall be
linked to solve optimisation problems faster or make their solutions
better usable (under realistic conditions).
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Applications of operations
research optimisation on business processes in general as well
as applications in economic, engineering and natural sciences.
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Analysis and modelling of
complex systems.
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Optimisation procedures
and optimisation potentials of complex systems.
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Combinatorial optimisation
and integer programming tools to handle complex systems
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Procedures of discrete
event and continuous time simulation.
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(Simulation-based)
heuristic and algorithmic procedures for efficiently solving
complex problems.
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Optimisation Models for
production planning and control, for operations and business
processes, for technological devices, for logistics and so on.
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Simulation Optimisation
methods.
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Simulation-based hybrid
optimisation techniques.
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Utilisation of simulation
to make optimisation problems and their (feasible) solutions
usable under industrial conditions.
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Proper handling of
uncertainty and the attainment of robust solutions.
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Methods of calibration,
validation and verification of models (under realistic
conditions).
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Tools for simulation and
optimisation: their more effective design for operating under
realistic conditions, especially concerning shorter runtimes, as
well as their architecture.
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Simulation in the areas of
production planning and control, logistics, transportation,
supply chain management, and processes
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Simulation and
optimisation models with consideration of sustainable aspects
(including the economical, ecological and social dimension)
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