https://github.com/aapeliv/simulation

https://github.com/aapeliv/simulation

Last synced: 7 days ago
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• Host: GitHub
• URL: https://github.com/aapeliv/simulation
• Owner: aapeliv
• Created: 2022-01-26T22:47:18.000Z (almost 3 years ago)
• Default Branch: develop
• Last Pushed: 2022-01-26T23:10:46.000Z (almost 3 years ago)
• Last Synced: 2024-11-17T13:49:55.015Z (2 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 1.23 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

        
# Recitations on Simulation using Python and Simpy

This [repo](https://github.com/aapeliv/simulation) contains recitations (hands-on lectures) on simulation. These were originally created for IEOR4404 *Simulation* at Columbia University in Fall 2021.

Some of these lectures do not make much sense without the accompanying recordings. Feel free to [contact me](https://www.aapelivuorinen.com) and I'll be happy to send you links to those recordings.

## Recitation 1: some sampling methods

* Accept-reject sampling

* Simple Monte-Carlo integration

* The Box-Muller method for sampling normal RVs

## Recitation 2: introduction to Python for Simulation

* Variables, flow control, data structures

* External libraries, numpy, matplotlib

## Recitation 3: diving into randomness

* 2D Monte Carlo integration

* Three ways to sample from Homogeneous Poisson processes

## Recitation 4: more Poisson processes and intro to queueing systems

* Sampling from 1D and 2D Poisson processes

* Simulating single-server queueing systems from scratch

## Recitation 5: non-homogeneous Poisson processes

* Sampling from non-homogeneous Poisson processes

* Revision for the mid-term exam

## Recitation 6: systems simulation with simpy

* Life sim

## Recitation 7: more systems simulation

* Simulation of a web app

## Recitation 8: antithetic systems simulation

* Simulating a café with antithetic variance reduction

## Recitation 9: variance reduction

* When the antithetic method fails

* Contorl variates

* Importance sampling

## Recitation 10: hyperparameter optimization

* An example of hyperparameter optimization with `hyperopt`