CBE 40455
Process Operations
CBE 40455 Process Operations
This repository comprises a collection of Jupyter/Python notebooks in support of CBE40455 taught at the University of Notre Dame.
The links below display the notebooks as regular HTML web pages. From there you can run the notebook on Google Colaboratory or download to run on your own laptop. To run on your own laptop you will need to install Jupyter and Python 3, such as the excellent Anaconda distribution from Continuum Analytics.
Please let me know (jeff at nd.edu) if you any thoughts or suggestions on how these notebooks could be improved for teaching and learning the principles of Process Operations.
Table of Contents
Chapter 1.0 Getting Started Guides
- 1.1 Getting Started with CVXPY
- 1.2 Getting Started with Gurobi
- 1.3 Getting Started with GNU MathProg in Jupyter Notebooks
- 1.4 Getting Started with Pandas
Chapter 2.0 Simulation of Discrete Event Systems
- 2.1 Getting Started with SimPy
- 2.2 Queuing Systems
- 2.3 Emergency Room Simulation
- 2.4 Model Development in SimPy
- 2.5 Extracting Information from Discrete-Event Simulations
- 2.6 Spankys Pizzeria
- 2.7 Warehouse Fulfullment Operations
- 2.8 Geometric Brownian Price Process
- 2.9 Continuous Time Simulation in SimPy
- 2.10 Decentralized Control in a Supply Chain
Chapter 3.0 Linear Optimization
Chapter 4.0 Scheduling
- 4.1 Critical Path Method
- 4.2 Machine Bottleneck
- 4.3 Job Shop Scheduling
- 4.4 Jesuit Volunteer Corps
- 4.5 Unit Commitment
- 4.6 Scheduling Multipurpose Batch Processes using State-Task Networks
Chapter 5.0 Logistics
- 5.1 Economic Order Quantity
- 5.2 Assignment Problems
- 5.3 Vehicle Routing
- 5.4 Vehicle Routing with Time Windows
- 5.5 Traveling Salesman Problem with Time Windows
- 5.6 Pickup and Delivery
- 5.7 Stock Cutting
Chapter 6.0 Optimization under Uncertainty
- 6.1 Newsvendor Problem
- 6.2 Scenario Analysis for a Plant Expansion
- 6.3 Risk Neutral Gambler
- 6.4 Risk Averse Gambler
- 6.5 Points after Touchdown Decision
Chapter 7.0 Risk and Diversification
- 7.1 Measuring Return
- 7.2 Geometric Brownian Motion
- 7.3 Binomial Model for Pricing Options
- 7.4 Real Options
- 7.5 Portfolio Optimization
- 7.6 Portfolio Optimization using Mean Absolute Deviation
- 7.7 Portfolio Optimization
- 7.8 Log-Optimal Growth and the Kelly Criterion
- 7.9 Log-Optimal Portfolios
Chapter 8.0 Optimization in Google Sheets
Chapter 9.0 Student Projects
License Requirements. The materials in this repository are available at https://github.com/jckantor/CBE40455.git for noncommercial use under terms of the Creative Commons Attribution Noncommericial ShareAlike License. You are invited to fork this repository, and to use, adapt, remix these material for non-commericial purposes. The license terms require you to give attribution and share your work under the same terms. Pull requests for corrections and additions to these materials are most welcome.