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Ordonnancement sous perturbations : cadre d'étude et approche d'évaluation de la robustesse par automates stochastiques

Abstract : The main objective of this thesis is to propose an approach to consider perturbations in the context of a production scheduling problem. The proposed approach emphasizes the importance of evaluating the performance of a scheduling in a disturbed environment. Production scheduling is an important and common problem in the world of industry and scientific research. In order to propose scheduling solutions, the suggested methods propose optimal scheduling to minimize or maximize a defined criterion. This objective has certainly been adopted for several years but no longer fully meets the dynamics of production workshops. Taking perturbations into account is therefore a major issue in the scheduling problem. To address this issue, after an introduction and state of the art, we propose, in the main body of the manuscript, the definition of the performance and appropriate approach to deal with the impact of perturbations in scheduling. Robustness is then identified as a suitable performance to assess this impact. Furthermore, specifying robustness allows to identify a formal framework to specify the different robustness problems that scheduling must face. To address the problem of scheduling robustness, we propose an evaluation process based on discrete-event system models. More precisely, stochastic timed automata and statistical model-checking are used to measure the robustness of a perturbed schedule. The evolution of production systems and their flexibility and agility constraints require that the evaluation approach must also be flexible and adaptable. The process proposed in this thesis allows not only its adaptation to several production workshop problems but also to take into account real decision situations in an industrial context. To illustrate the feasibility and applicability of this process, the UppAal SMC tool is used.
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Submitted on : Friday, February 26, 2021 - 12:57:43 PM
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Sara Himmiche. Ordonnancement sous perturbations : cadre d'étude et approche d'évaluation de la robustesse par automates stochastiques. Automatique / Robotique. Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0177⟩. ⟨tel-03153444⟩

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