%0 Conference Proceedings
%T Hybridization of mixed-integer linear program and discrete event systems for robust scheduling on parallel machines
%+ Centre de Recherche en Automatique de Nancy (CRAN)
%+ Systèmes Logistiques et de Production (LS2N - équipe SLP  )
%+ Département Automatique, Productique et Informatique (IMT Atlantique - DAPI)
%+ Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS)
%A Aubry, Alexis
%A Marangé, Pascale
%A Lemoine, David
%A Himmiche, Sara
%A Norre, Sylvie
%Z Published in Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 630 , pp. 73-80, Springer, Cham, 2021Part II - Hybrid Approaches for Production Planning and Scheduling
%< avec comité de lecture
%@ 978-3-030-85873-5
%Z ISET
%( IFIP WG 5.7 International Conference, APMS 2021, Advances in Production Management Systems
%B International Conference on Advances in Production Management Systems, APMS 2021
%C Nantes, France
%Y Alexandre Dolgui
%Y Alain Bernard
%Y David Lemoine
%Y Gregor von Cieminski
%Y David Romero
%I Springer International Publishing
%3 IFIP Advances in Information and Communication Technology
%V AICT-630
%N Part II
%P 73-80
%8 2021-09-05
%D 2021
%R 10.1007/978-3-030-85874-2_8
%K Discrete event systems
%K Parallel machines
%K Robust scheduling
%K Robust mixed integer programming model
%Z Computer Science [cs]/Operations Research [math.OC]Conference papers
%X 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.
%G English
%Z TC 5 ; WG 5.7
%2 https://hal.science/hal-03337509/document
%2 https://hal.science/hal-03337509/file/509923_1_En_8_Chapter.pdf
%L hal-03337509
%U https://hal.science/hal-03337509
%~ UNIV-NANTES
%~ INSTITUT-TELECOM
%~ PRES_CLERMONT
%~ CNRS
%~ EC-NANTES
%~ CRAN-ISET
%~ CRAN
%~ LIMOS
%~ UNAM
%~ IFIP
%~ IFIP-AICT
%~ UNIV-LORRAINE
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-APMS
%~ IFIP-WG5-7
%~ LS2N
%~ LS2N-SLP
%~ LS2N-SLP-IMTA
%~ IMTA_DAPI
%~ LS2N-IMTA
%~ IMT-ATLANTIQUE
%~ INSTITUTS-TELECOM
%~ TEST-HALCNRS
%~ CLERMONT-AUVERGNE-INP
%~ LS2N-MODELIS-IMTA
%~ NANTES-UNIVERSITE
%~ UNIV-NANTES-AV2022
%~ NU-CENTRALE
%~ TEST3-HALCNRS
%~ IFIP-AICT-630
%~ CRAN-MPSI