Transcription of Simulation Programming with Python - Northwestern …
{{id}} {{{paragraph}}}
Chapter 4 Simulation Programmingwith PythonThis chapter shows how simulations of some of the examples in Chap. 3 can beprogrammed using Python and the SimPy Simulation library[1]. The goals ofthe chapter are to introduce SimPy, and to hint at the experiment design andanalysis issues that will be covered in later chapters. While this chapter willgenerally follow the flow of Chap. 3, it will use the conventions and patternsenabled by the SimPy SimPy OverviewSimPy is an object-oriented, process-based discrete-event Simulation library forPython. It is open source and released under the M license. SimPy providesthe modeler with components of a Simulation model including processes, foractive components like customers, messages, and vehicles, and resources, forpassive components that form limited capacity congestion points like servers,checkout counters, and tunnels.
reactivate(): reactive a previously passivated process cancel(): cancels all events associated with a previously passivated process. The functions activate(), reactivate(), and cancel() can also be called within processes as needed. 4.2 Simulating the M(t)=M=1Queue Here we consider the parking lot example of Sect. 3.1a queueing system with
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
{{id}} {{{paragraph}}}