Planning and scheduling optimization are important in the context of workforce management. In this context, it is necessary to follow legal and regulatory constraints and to deal with companies’ requirements. This thesis aims to build a system that is able to take care of this problem.
In spite of similarities with the usual scheduling problems, our context imposes new difficulties: task durations are not always known but must be worked out according to the constraints and the preferences; some constraints must be necessarily satisfied while others are related to preferences that need to be satisfied “as well as possible”.
The purpose of this project is to explore different approaches (heuristics, metaheuristics …) in order to solve various scheduling problems.
To reach this aim, two objectives have been defined. The first is to elaborate a modeling language allowing each company to easily express their scheduling problem. The second is to develop an engine able to solve modeled problems. This engine should adapt to the different characteristics of each problem to provide a good solutions while respecting deadlines.