Today more than ever, the optimal use of resources has become a very important issue. Many decision problems (logistics, production, space, etc.) aiming at an optimal use of resources can be formulated as constraint combinatorial optimization problems. Unfortunately, these problems are difficult to solve mainly for two reasons :

1. They require complex algorithms to design and develop,
2. Finding an optimal solution can be computationally intensive.

In this course, we will learn the basics of constraint programming: a paradigm that aims to reduce the cost of developing and solving combinatorial problems through extensive reuse of code, whose design is open-ended, but also through pruning techniques of the search space by reasoning at the level of constraints.

During the proposed projects, you will develop your own constraint programming solver in Java that we will gradually extend in functionality in order to solve more and more complex combinatorial problems, especially in scheduling and vehicle routing. You will also develop global constraints, implement search strategies, model problems, and measure the impact of modeling choices on the efficiency of the solution.

Each module first introduces the concepts through videos, then a programming project is proposed to put these concepts into practice.