The queuing theory is an important area within the stochastics. Queues occur in many situations in production and logistics and are usually undesirable because of the need of temporary storage of semi-finished components and because storage will employ capital. If customers will have to wait for a longer period of time this can have a negative impact on the company's image or have concrete material losses, if people give up waiting prematurely and thus they are lost as a customer.
Due to stochastic influences in both the inter-arrival times of customers as well as the service times there can be no simple relationship between arrival and service rate on the one side and the waiting time on the other side. Methods for studying the stochastic processes will be needed here.
TU Clausthal offers a number of simulation programs via the Simulation Science Center. These are all open source programs that can be used free of charge:
Warteschlangensimulator allows the simulation of any complex queueing network. The models are defined in Warteschlangensimulator in the form of flowcharts. Optionally, an animation can be displayed during the simulation of the models to illustrate the movement of the customers through the system. For the automated examination of different models, parameter series can be created automatically and an optimizer is also available. Furthermore, external data sources can be connected directly during the simulation of models and (partial) results can also be transferred directly to external programs (e.g. databases).
Download:
Warteschlangensimulator requires a Java runtime environment and was published as open source.
Callcenter Simulator is designed to map real call center systems consisting of several sub-call centers, different caller groups, different agent groups (with different skill levels and different shift plans), complex assignment rules, etc. It can be used directly for staff requirements planning and for the analysis of possible control strategies in large call center networks. In addition to pure simulation, the program also provides functions for automatic optimization of the number of agents.
Download:
Callcenter Simulator requires a Java runtime environment and has been published as open source.
Mini Callcenter Simulator essentially reproduces the same G/G/c/K+G model that the webapp contains. However, it has much more probability distributions that can be used for inter-arrival times, service times, post-processing times, waiting time tolerances and repeat distance distributions. In addition, considerably more characteristics are recorded and various export options are available for the simulation results. Furthermore, the simulation results can be directly compared to corresponding Erlang-C results and explanations can be displayed why deviations occur at which points.
Download:
Mini Callcenter Simulator requires a Java runtime environment and has been published as open source.
The Mini Simulator is a web app fully implemented in Javascript that can be run in any modern browser (including tablets and smartphones). The app maps a G/G/c/K+M model, i.e. a model consisting of a queue and a operating station. Batch arrivals, batch operations, customer impatience, repeaters and forwarding can be mapped.