Hybridization of mixed-integer linear program and discrete event systems for robust scheduling on parallel machines
Résumé
This paper proposes an approach for robust scheduling on parallel machines. This approach is based on a combination of robust mathematical and discrete event systems models which are iteratively called in order to converge towards a schedule with the required robustness level defined by the decision maker. Experimentations on a small instance (10 jobs and 2 unrelated machines) and a more complex one (30 jobs and 6 uniform machines) show that this approach permits to converge quickly to a robust schedule even if the probability distribution associated to the uncertainties are not symmetrical. The approach achieves a better rate of convergence than those of the literature’s methods.
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