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ND Pyomo Cookbook
1. Getting Started with Pyomo
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. Linear Programming
2.1. Production Models with Linear Constraints
2.2. Production Model Sensitivity Analysis
2.3. Linear Blending Problem
2.4. Design of a Cold Weather Fuel for a Camping Stove
2.5. Gasoline Blending
2.6. Model Predictive Control of a Double Integrator
2.7. Non-Continuous Objectives
3. Assignment Problems
3.1. Transportation Networks
4. Scheduling with Disjunctive Constraints
4.1. Introduction to Disjunctive Programming
4.2. Machine Bottleneck
4.3. Job Shop Scheduling
4.4. Maintenance Planning
4.5. Scheduling Multipurpose Batch Processes using State-Task Networks
4.6. Unit Commitment
5. Simulation
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
5.4. Diffusion with Adsorption in Polymers
6. Differential-Algebraic Equations
6.1. Unconstrained Scalar Optimization
6.2. Maximizing Concentration of an Intermediate in a Batch Reactor
6.3. Path Planning for a Simple Car
6.4. Soft Landing Apollo 11 on the Moon
6.5. Ascent from Lunar Surface
7. Parameter Estimation
7.1. Parameter estimation
8. Financial Applications
8.1. Obtaining Historical Stock Data
8.2. Consolidating and Charting Stock Data
8.3. Binomial Model for Pricing Options
8.5. MAD Portfolio Optimization
8.6. Real Options
9. Guide to Coding with Pyomo
9.1. Notebook Style Guide
10. Index
Colab
Repository
Open issue
.ipynb
.pdf
Scheduling with Disjunctive Constraints
4.
Scheduling with Disjunctive Constraints
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