Robust Strategic Planning of Phytosanitary Treatments in Agriculture

Ayşe N Arslan (1, 2) , Boris Detienne (3, 4)

1 INSA Rennes - Institut National des Sciences Appliquées - Rennes
2 IRMAR - Institut de Recherche Mathématique de Rennes
3 Realopt - Reformulations based algorithms for Combinatorial Optimization
4 IMB - Institut de Mathématiques de Bordeaux

This paper deals with robust planning and scheduling of activities in agriculture and in particular the application of phytosanitary treatments. The crops are subject to many diseases that may arise during different time windows of the planning horizon. In response, a phytosanitary treatment can be applied to protect against a subset of these diseases. However, the effective duration of some treatments is uncertain, it depends on the type of treatment applied as well as on the weather conditions. In this study we introduce a penalty function based approach to handle this uncertainty without being overly conservative akin to light robustness approach proposed in the literature. We discuss different forms for this penalty function and elaborate on solution methodologies for the resulting models. We test the effectiveness of our approach with realistically-sized instances, which correspond to a typical vineyard in Bordeaux area, and present a numerical analysis of different optimization models and solution methods.

Mots clés: Robust optimization; Light robustness; Penalty function; Phytosanitary treatment planning

Domaines: Optimisation et contrôle [math.OC]

Ayşe N Arslan, Boris Detienne. Robust Strategic Planning of Phytosanitary Treatments in Agriculture. 2021. ⟨hal-03410635⟩