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Sim-optimization hybrid approach for scheduling randomly deteriorating treatment tasks in horticulture

Article dans une revue avec comité de lecture
Author
ccMAZAR, Merouane
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
1059165 Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires [LINEACT]
BETTAYEB, Belgacem
470176 CESI : groupe d’Enseignement Supérieur et de Formation Professionnelle [CESI]
1059165 Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires [LINEACT]
KLEMENT, Nathalie
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
SAHNOUN, Mhammed
1059165 Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires [LINEACT]
ccLOUIS, Anne
1059165 Laboratoire d'Innovation Numérique pour les Entreprises et les Apprentissages au service de la Compétitivité des Territoires [LINEACT]

URI
http://hdl.handle.net/10985/22944
DOI
10.1016/j.ifacol.2022.09.449
Date
2022-10
Journal
IFAC-PapersOnLine

Abstract

In this paper, we study the problem of scheduling robotized tasks in the context of Agriculture 4.0. The objective is to optimize the treatment tasks of plants against an evolving disease (mildew) within a greenhouse. The treatment is performed using a type-C ultraviolet radiation (UV-C) by an UV-Robot. We propose a semi-dynamic simulation-optimization approach based on a Markovian model of the disease behavior in the greenhouse. Two variants of simulation-optimization hybridization are tested and analyed.

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