ND Pyomo Cookbook is a collection of notebooks showing how to use Pyomo to solve modeling and optimization problems. With Pyomo, one can embed within Python an optimization model consisting of decision variables, constraints, and an optimization objective. A rich set of features enables the modeling and analysis of complex systems.
The notebooks in this collection were developed for instructional purposes at Notre Dame. Originally developed using the Anaconda distribution of Python, the notebooks have been updated to open directly Google Colaboratory where they can be run using only a browser window.
PyomoFest at Notre Dame was held June 5-7, 2018. This repository contains the agenda, slides and exercises distributed during that event.
- 1.1 Installing a Pyomo/Python Development Environment
- 1.2 Running Pyomo on Google Colab
- 1.3 Running Pyomo on the Notre Dame CRC Cluster
- 1.4 Cross-Platform Installation of Pyomo and Solvers
- 2.1 Production Models with Linear Constraints
- 2.2 Linear Blending Problem
- 2.3 Design of a Cold Weather Fuel for a Camping Stove
- 2.4 Gasoline Blending
- 2.5 Model Predictive Control of a Double Integrator
- 4.1 Machine Bottleneck
- 4.2 Job Shop Scheduling
- 4.3 Maintenance Planning
- 4.4 Scheduling Multipurpose Batch Processes using State-Task Networks
- 4.5 Unit Commitment
- 5.1 Response of a First Order System to Step and Square Wave Inputs
- 5.2 Exothermic CSTR
- 5.3 Transient Heat Conduction in Various Geometries
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent