EURO 2024 Copenhagen
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1013. Modeling a harvest planning and scheduling problem in a hierarchical agrifood supply chain by bilevel programming

Invited abstract in session MA-12: Optimization in Agriculture, stream OR in Agriculture and Forestry .

Monday, 8:30-10:00
Room: 13 (building: 116)

Authors (first author is the speaker)

1. Victor M. Albornoz
Departamento de Industrias, Universidad Tecnica Federico Santa Maria

Abstract

The contribution addresses a harvest planning problem in the context of a hierarchical agrifood supply chain, which integrates the definition of management zones for harvesting, the harvest scheduling problem and the coordination between the producer and the wholesaler. The problem is represented through bilevel programming models that allow the representation of the hierarchy between the producer (leader) and a wholesaler (follower). The producer plans and schedules the harvest of the different homogeneous management zones into the resulting partition of the farm and the production levels to be offered to each wholesaler, while the wholesaler decides the quantity of product to be purchased to satisfy the demand requirements. First of all, a mixed–integer bilevel program is proposed and solved alternatively using an algorithmic strategy based on the Benders decomposition method. Then, a stochastic bilevel program is also proposed for representing the uncertainty in future crop yields, prices, and demands, using a finite set of scenarios. The bilevel optimization models considered are reformulated into mixed-integer linear programs using the Karush–Kuhn–Tucker conditions and replacing the nonlinear complementary constraints by the big-M method. The models were applied in a Case Study for selective harvesting of grapes with data collected from a farm. The results obtained when solving a set of instances highlight the importance of the problem and the proposed methodology.

Keywords

Status: accepted

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