Sim-optimization hybrid approach for scheduling randomly deteriorating treatment tasks in horticulture
Article dans une revue avec comité de lecture
Author


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]

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]
Date
2022-10Journal
IFAC-PapersOnLineAbstract
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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