After following this course, students are able to
- apply analytic results for open and closed queueing models with exponentially distributed inter-arrival and service times and about approximations for systems with general distributed service times, especially for non-product form networks.
- apply (generalized) Mean-value techniques.
- apply Quasi Birth Death processes.
- apply general manufacturing systems with set-ups and break-downs and about workload control.
- model a(n idealized) practical situation as a network of queues.
- numerically find and evaluate (approximations for) performance measures.
- to critically interpret numerical results for approximated performance measures.
Stochastic models are of great importance for the design, planning and control of manufacturing systems such as, for instance, logistic networks with production or distribution stages, where each stage is modelled as either an open or a closed queueing network. In this course, we focus on a variety of models to describe, analyze and optimize a broad range of manufacturing systems. These models can be characterized as combinations of queueing models and inventory models.|
This course is taught together with Stochastic Models in Production and Logistics (191531830). The assignments in AQM are more mathematically oriented.