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Coopération homme-machine pour l'ordonnancement sous incertitudes

Abstract : Most of the research in scheduling is based on determinism models, not adapted to the reality of shop scheduling. Indeed, manufacturing systems are subject to uncertainties. This is why scheduling under uncertainties is a booming field.

Moreover, humans are not taken into account in most of the scheduling methods. However, humans have a central role in the scheduling process, and their knowleadges are precious. This is why we think that efficient human-machine systems is indispensible for an efficient scheduling process.

To achieve this goal, group sequencing is used. This scheduling method has different advantages : it is made to manage the uncertainties present in the shop floor, and its structure is easy to use by the human. We study existing human-machine systems for group sequencing. Then, we propose a new system to improve the cooperation between human and machine. In this new human-machine system, we use the best case quality in a group sequence. Because this subject is not studied by the literature, we propose lower bounds, heuristics and an exact method to solve this problem.
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Contributor : Guillaume Pinot <>
Submitted on : Thursday, August 13, 2009 - 5:37:54 PM
Last modification on : Friday, October 23, 2020 - 4:38:15 PM
Long-term archiving on: : Monday, October 15, 2012 - 4:11:00 PM


  • HAL Id : tel-00409897, version 1



Pinot Guillaume. Coopération homme-machine pour l'ordonnancement sous incertitudes. Autre [cs.OH]. Université de Nantes, 2008. Français. ⟨tel-00409897⟩



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