← Back
Other
Python

sim-tools


Summary

Tools to support Discrete-Event Simulation (DES) and Monte-Carlo Simulation education and practice.

Authors
Affiliation

Tom Monks

University of Exeter

Amy Heather

University of Exeter

Alison Harper

University of Exeter

Package to support discrete-event simulation (DES) and monte-carlo simulation education and applied simulation research. Features:

  1. Implementation of classic Optimisation via Simulation procedures such as KN, KN++, OBCA and OBCA-m

  2. Theoretical and empirical distributions module that includes classes that encapsulate a random number stream, seed, and distribution parameters.

  3. An extendable Distribution registry that provides a quick reproduible way to parameterise simulation models.

  4. Implementation of Thinning to sample from Non-stationary Poisson Processes (time-dependent) in a DES.

  5. Automatic selection of the number of replications to run via the Replications Algorithm.

  6. EXPERIMENTAL: model trace functionality to support debugging of simulation models.

sim-tools logo


Project status

Status: Gold

Rationale: Python package with documentation website and test suite.