Project CPFLOW

Minimizing average and weighted tardiness in constraint-based scheduling

About the project

The project focuses on improving constraint-based scheduling models to handle more effectively lesser-studied objective functions such as average tardiness or weighted tardiness. Although scheduling is a central topic in industrial production and computer science, most research concentrates on minimizing total tardiness, leaving other criteria, despite being common in practice, less well supported.
Constraint programming offers a powerful framework for modeling these problems, but it has historically been geared toward finding feasible solutions rather than optimizing complex objective functions. Therefore, efficiently optimizing these objectives represents a scientific challenge, and the project aims to develop new theoretical and algorithmic approaches to better integrate these objective functions, thereby expanding the capabilities of constraint-based scheduling tools.
In addition, several project partners are involved in science-outreach initiatives, notably within Terra Numerica. In this context, the creation of educational materials will help disseminate knowledge about constraint programming, operations research, and more specifically scheduling methods and graph theory to a broad audience.