Stochastic Models in Production and Logistics


Random phenomena are common in natural and man-made systems. For examples: unexpected machine failures can be observed in many production systems or uncertain transportation times can lead to delayed deliveries. It is important to understand the random behavior of systems and to be able to model such systems in order to study their performance. These models can be used to investigate measures to mitigate the effect of uncertainties or to design and control systems in such a way that a specific performance of the system can be obtained. The following topics are discussed:

  • Discrete time Markov Chains
  • Continuous time Markov Chains
  • Stochastic models of manufacturing systems
  • Queuing systems
  • Inventory systems

Previous Knowledge:

Fundamentals in Probability Theory

Last Modification: 24.04.2019 - Contact Person: Webmaster