PYCSP3: Modeling Combinatorial Constrained Problems in Python

09/01/2020 ∙ by Christophe Lecoutre, et al. ∙ 33

In this document, we introduce PYCSP3, a Python library that allows us to write models of combinatorial constrained problems in a simple and declarative way. Currently, with PyCSP3, you can write models of constraint satisfaction and optimization problems. More specifically, you can build CSP (Constraint Satisfaction Problem) and COP (Constraint Optimization Problem) models. Importantly, there is a complete separation between modeling and solving phases: you write a model, you compile it (while providing some data) in order to generate an XCSP3 instance (file), and you solve that problem instance by means of a constraint solver. In this document, you will find all that you need to know about PYCSP3, with more than 40 illustrative models.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 12

page 20

page 25

page 26

page 30

page 32

page 35

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.