Constraint Programming Winter School
Topic outline
-
General
-
If you continue to work on the labs and you have questions, you can push your code in the lab so we can access it and contact us:
- Hadrien: hadrien.cambazard@grenoble-inp.fr
- Arnaud: arnaud.malapert@univ-cotedazur.fr
- Charles: charles.prudhomme@imt-atlantique.fr
-
In this tutorial, we are going to code a minimalist constraint solver.
Such a minimalist constraint solver is designed with simplicity in mind, focusing on essential functionalities to solve constraint satisfaction problems (CSPs) with the aim of understanding how it works.
Its design revolves around a lightweight architecture, implemented in Python, a compact programming language. The solver prioritizes fundamental constraint propagation techniques and basic search algorithms to efficiently explore the solution space without consideration about memory or computational requirements.
By eschewing unnecessary features and optimizations, the minimalist constraint solver offers a lightweight and easy-to-understand solution for solving a variety of combinatorial problems, making it suitable for applications where simplicity and speed are paramount.