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d-krupke/cpsat-primer

An open-access book-style primer teaching how to model and solve combinatorial optimization problems with Google OR-Tools' CP-SAT solver.

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What is it?

The CP-SAT Primer is a free, book-style tutorial for learning Google OR-Tools' CP-SAT solver, a constraint programming and SAT-based solver for combinatorial optimization. It is written for computer science students and developers, with Python examples throughout, and it compares CP-SAT with mixed integer programming (MIP) solvers and other optimization tools.

The first part covers installation, a first model, basic modeling of variables, objectives and constraints, advanced constraints such as circuit, interval and reservoir constraints, solver parameters, and how to read the solver log. The second part addresses practical engineering topics: coding patterns for maintainable optimization code, serving optimization jobs through an API, large neighborhood search heuristics, and benchmarking models.

The primer is maintained by Dominik Krupke at TU Braunschweig and is released under CC-BY 4.0, with a companion website that renders the same content as a book.

Key features

  • 01Covers CP-SAT basics: variables, objectives, linear and logical constraints.
  • 02Explains advanced constraints such as circuit, interval, and no-overlap.
  • 03Shows how to set time limits, hints, and parallelism in the solver.
  • 04Teaches interpreting the solver log to judge solution quality.
  • 05Compares CP-SAT with MIP solvers and other optimization techniques.
  • 06Includes Python code examples and a section on large neighborhood search.

Use cases

  • Learning combinatorial optimization as a computer science student.
  • Moving from a MIP solver to CP-SAT for scheduling or routing models.
  • Building a maintainable optimization service with CP-SAT behind an API.
  • Benchmarking and tuning a CP-SAT model for a production problem.

Quick start

  1. 1

    Install OR-Tools with pip

    pip install -U ortools
  2. 2

    Copy the Knapsack example from the README and run it in Python

Topics

#optimization#constraint-programming#operations-research#ortools#combinatorial-optimization#python#tutorial#cp-sat

FAQ

What is cpsat-primer?
An open-access book-style primer teaching how to model and solve combinatorial optimization problems with Google OR-Tools' CP-SAT solver. The CP-SAT Primer is a free, book-style tutorial for learning Google OR-Tools' CP-SAT solver, a constraint programming and SAT-based solver for combinatorial optimization. It is written for computer science students and developers, with Python examples throughout, and it compares CP-SAT with mixed integer programming (MIP) solvers and other optimization tools.
Is cpsat-primer free to use? What license does it have?
cpsat-primer is open source under the CC-BY-4.0 license. Check the license terms before using it in commercial products.
Is cpsat-primer still maintained?
Updated within 6 months. The last commit to cpsat-primer was on Sep 6, 2026.
What can I use cpsat-primer for?
Learning combinatorial optimization as a computer science student. Moving from a MIP solver to CP-SAT for scheduling or routing models. Building a maintainable optimization service with CP-SAT behind an API. Benchmarking and tuning a CP-SAT model for a production problem.
How do I install cpsat-primer?
Install OR-Tools with pip: pip install -U ortools Copy the Knapsack example from the README and run it in Python
Where can I get cpsat-primer?
The source code and installation instructions are on GitHub: https://github.com/d-krupke/cpsat-primer

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