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discopt

Tutorials — Problem Classes

Linear Programming
Quadratic Programming
Mixed-Integer Linear Programming (MILP)
0-1 Knapsack: Packing a Backpack
Mixed-Integer Quadratic Programming (MIQP)
Mixed-Integer Nonlinear Programming (MINLP)
Generalized Disjunctive Programming (GDP)
Dynamic Optimization with DAE Collocation
Robust Optimization
Adjustable Robust Optimization
Multi-Objective Optimization

Tutorials — Solver Backends

Outer Approximation Solver
Certified-global MINLP with AMP
Pure-JAX Interior Point Method
ripopt: Rust Interior Point Method
ripopt v0.3.0: Parametric Sensitivity Analysis (sIPOPT)
cyipopt: The Ipopt Solver Backend
Solver Backend Selection Guide

Tutorials

discopt Quickstart Tutorial
Modeling Guide: Expressive vs. Fast Construction
discopt MINLP Examples
Problem Class Auto-Detection in discopt

Advanced Features

discopt Advanced Features
Solver Internals: BARON-Parity Features
Presolve
Parametric Sensitivity Analysis (sIPOPT-style)
LLM Integration
LLM Integration
Warm-Starting with Initial Solutions
Convex NLP Fast Path
Convexity detection
Nonlinear Branch & Bound (NLP-BB)
Exporting Models to MPS and LP Formats
Callbacks and User-Defined Cuts

Solver Backends

QP Solver Backend: HiGHS
NLP Backend Comparison: ripopt vs IPM vs Ipopt
Batch IPM (vmap) vs Sequential Ipopt
Benchmarks by Problem Class
Benchmark Dashboard

Applications

Neural Network Embedding
Decision-Focused Learning with discopt
Parameter Estimation & Design of Experiments
Parameter Estimation
Model-Based Design of Experiments
Design of Experiments from the Command Line
Batch / Parallel Design of Experiments
Mixture Designs
Latin-Square Designs and ANOVA
Factor Screening with 2-Level Factorial Designs
Active-Learning Optimization with a Surrogate
Model-Based Active Learning for Response Optimization
Identifiability and Estimability Analysis
Model Discrimination Workflow

API Reference

API Reference
- discopt

Appendix

Comparison of Optimization Frameworks
References

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By John Kitchin

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