Abstract:
Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and c...Show MoreMetadata
Abstract:
Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and complex systems. Therefore, there are a variety of commercial (Simio, AnyLogic, Simul8, Arena, etc.) and non-commercial (SimPy, Salabim, etc.) software packages that enable users to take advantage of DES modeling. Although these tools are capable of modeling real-life systems with a high accuracy, they generally fail to conduct advanced analytical analysis (i.e., machine learning, interactive visualizations) or complicated optimization (i.e., simheuristics). Therefore, coupling these DES platforms with external programming languages like Python offers additional mathematical operations and algorithmic flexibility. This integration makes the simulation modeling more intelligent and extends its applicability to a broader range of problems. This study aims to provide a step-wise tutorial for helping simulation users to create intelligent DES models by integrating them with Python. Multiple demo examples are discussed to provide insights and making this connection based on commercial and non-commercial DES packages.
Published in: 2021 Winter Simulation Conference (WSC)
Date of Conference: 12-15 December 2021
Date Added to IEEE Xplore: 23 February 2022
ISBN Information: