<p>Master's student or engineering graduate with solid knowledge of mathematical modelling and programming.</p>
<p>please send a cover letter, CV and transcripts to : <a href="mailto:martin.krejca@polytechnique.edu">martin.krejca@polytechnique.edu</a></p>
<p>The scheduling problem at hand is concerned with the automated management of development processes in companies. In such processes, different projects are split into smaller parts (such as work elements or tasks), which need to be assigned to different teams. Each team has various skills and capacities, and each task has a priority, a start and an end date, a cost, and other factors. The aim is to assign the different parts of each project to the teams such that all constraints are satisfied and that the overall time spent on the projects is minimized.</p><p>Due to various constraints as well as the diverse nature of projects and set-up of teams, this problem is challenging. To this end, heuristic solvers are employed, which provide a great compromise between finding good solutions and reducing the run time of the solver. At the moment, Konatus uses an evolutionary algorithm as a heuristic solver. This algorithm acts as the baseline for the internship. <strong>The goal of the internship is to come up with an improved heuristic solver for the scheduling problem.</strong> This new algorithm can be tested on different data sets provided by Konatus (both artificial and from the real world).</p>