QPLEX

QPLEX is a computational methodology for modeling and analyzing a broad class of nonstationary stochastic systems. QPLEX has the following features:

• It calculates full probability distributions, not only means and variances.
• It calculates probability distributions over time, also known as transient distributions.
• It is tailor-made for optimization since its output is deterministic.
• It can analyze many system configurations and answer what-if questions since it is fast.
• It can calculate joint and conditional distributions corresponding to different times.
• It can incorporate observation data (e.g., measurements over time) to make predictions about future system performance.
• It can use observation data to analyze multiple models and calculate updated posterior probabilities for each of the models as data becomes available.

The animation above shows transient probability distributions of the number of entities in a multiserver queueing system experiencing a momentary surge in demand. These probability distributions were computed using the QPLEX Python Package.