Wednesday 27 November 2019, 1:00pm to 2:00pm
VenueCharles Carter A02 - View Map
Open toAlumni, Postgraduates, Staff
RegistrationRegistration not required - just turn up
The traditional use of simulation in Operational Research is in system design, either for studying systems or making tactical and strategic level decisions. This has been mirrored in the aims of simulation optimisation. In this case, once a decision has been made, the simulation will not be used again. It almost becomes irrelevant whether the simulation did a good job or not, as the stakeholders must make the best of the decision made. In the last 20 years, simulation (and simulation optimisation) has been used for operational decisions in Decision Support Systems. The model is reused repeatedly. So if the simulation is consistently producing poor predictions due to some systematic error, the results could be very costly. Thus, detecting this discrepancy becomes important. Due to natural variability in the system and simulation, this is not a trivial problem. It is complicated further by the decisions being heterogeneous and only getting one observation from the real world. This talk will present early work on a method for detecting systematic error in a simulation using a series of decisions.
My PhD is working with Rolls Royce to develop a Symbiotic Simulation system to help in airline disruption recovery. Disruption due to mechanical problems, crew sickness and weather can cause severe problems to airline businesses with knock-on effects being very costly. When reacting to this disruption, it is important to revise the flight schedule over the immediate future to help minimise the cost. The inherent stochasticity and complexity of the environment means that simulation modelling is
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