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Theses

The Group Cumulative Scheduling Problem

Abstract : The Infologic company develops an ERP, called Copilote, specialized for companies in the agri-food sector. It integrates several modules which allow to schedule different operations of the supply chain. These modules provide solutions to different scheduling problems with different constraints and objectives. Moreover, although the literature on scheduling problems is vast, a particular constraint encountered by Copilote users can only be modelled with difficulty using the elements known from the literature. In the problem encountered, the operations to be scheduled are divided into groups. The schedule must satisfy a constraint on these groups ensuring that at any given time there are no more than k groups such that some operations of these groups have been started while some others have not been completed. In this thesis, we study this new scheduling problem from a theoretical point of view, and we propose adaptations for the methods classically used for scheduling problems (integer linear programming, constraint programming, ant colony optimization, and local search). We also introduce a new approach hybridizing constraint programming and ant colony optimization to solve this problem. We experimentally compare these different algorithms on a test set constructed from real data, and we show that the best algorithm changes depending on the features of the instance to be solved. We then propose a method, which, depending on the features of the instance to be solved, automatically chooses the most suitable solving method. Finally, we evaluate, in a dynamic context, the cost of disrupting as little as possible the already established schedules when new data are revealed.
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https://hal.archives-ouvertes.fr/tel-03266690
Contributor : Abes Star :  Contact
Submitted on : Tuesday, October 26, 2021 - 4:43:10 PM
Last modification on : Wednesday, October 27, 2021 - 4:04:50 AM

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  • HAL Id : tel-03266690, version 2

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Lucas Groleaz. The Group Cumulative Scheduling Problem. Computer Science [cs]. Université de Lyon, 2021. English. ⟨NNT : 2021LYSEI035⟩. ⟨tel-03266690v2⟩

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