David Duvivier

Learn More
This paper deals with discrete-continuous problems of planning and scheduling nonpreemptable jobs. The need of reusability and modularity leads us to build a " generic " simulation and optimization framework, which is described in this contribution. The validation of our platform is presented in terms of an application to a real highly constrained(More)
Path planning is the way of determination of a collision free path between start and goal position through obstacles cluttered in a workspace. Though it is a complex problem, but it is an essential task for the navigation and controlling the motion of autonomous robot manipulators. This NP-complete problem (those problems is difficult to solve specially in(More)
This paper deals with multicriteria discrete-continuous problems of scheduling nonpreemptable jobs. The need for reusability and modularity leads us to build a " generic " optimisation and simulation framework, while the need to quickly generate good compromises between conflicting objectives requires the implementation of multicriteria scheduling models.(More)
| The tness function is generally deened rather straightforwardly in evolutionary algorithms (EA): it is simply the value of the function to optimize. In this paper, we argue and show that embedding more information in the tness function leads to a sig-niicant improvement of the quality of the local optima that are reached. The technique is developed here(More)