CBE60499

Table of Contents

Data Index

Figure Index

Python Module Index

Tag Index

Chapter 1.0 Getting Started with Pyomo

• 1.1 60 Minutes to Pyomo: An Energy Storage Model Predictive Control Example
• 1.2 Pyomo Mini-Project: Receding Horizon Stochastic Control

Chapter 2.0 Optimization Modeling with Applications

• 2.1 Continuous Optimization
• 2.2 Integer Programs
• 2.3 Logical Modeling and Generalized Disjunctive Programs
• 2.4 Dynamic Optimization: Differential Algebraic Equations (DAEs)
• 2.5 Numeric Integration for DAEs
• 2.6 Dynamic Optimization with Pyomo.DAE
• 2.7 Stochastic Programming
• 2.8 Parameter estimation with parmest
• 2.9 Supplementary material: data for parmest tutorial
• 2.10 Pyomo Homework 1
• 2.11 Pyomo Homework 2
• 2.12 Pyomo Homework 3

Chapter 3.0 Unconstrained Nonlinear Optimization: Theory and Algorithms

• 3.1 Linear Algebra Review and SciPy Basics
• 3.2 Mathematics Primer
• 3.3 Unconstrained Optimality Conditions
• 3.4 Newton-type Methods for Unconstrained Optimization
• 3.5 Quasi-Newton Methods for Unconstrained Optimization
• 3.6 Descent and Globalization
• 3.7 Algorithms Homework 1
• 3.8 Algorithms Homework 2
• 3.9 Algorithms Homework 3

Chapter 4.0 Constrained Nonlinear Optimization: Theory and Applications

• 4.1 Convexity Revisited
• 4.2 Local Optimality Conditions
• 4.3 Analysis of KKT Conditions
• 4.4 Constraint Qualifications
• 4.5 Second Order Optimality Conditions
• 4.6 NLP Diagnostics with Degeneracy Hunter
• 4.7 Simple Netwon Method for Equality Constrained NLPs
• 4.8 Inertia-Corrected Netwon Method for Equality Constrained NLPs
• 4.9 Algorithms Homework 4: Interior Point Methods

Chapter 5.0 Special Topics

• 5.1 Integer Programming with Simple Branch and Bound
• 5.2 MINLP Algorithms
• 5.3 Deterministic Global Optimization
• 5.4 Bayesian Optimization