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Solving the Crop Allocation Problemusing Hard and Soft Constraints

Published online by Cambridge University Press:  18 April 2013

Mahuna Akplogan
Affiliation:
INRA, UR 875 Biométrie et Intelligence Artificielle, 31326 Toulouse. [email protected], [email protected], [email protected], [email protected]
Simon de Givry
Affiliation:
INRA, UR 875 Biométrie et Intelligence Artificielle, 31326 Toulouse. [email protected], [email protected], [email protected], [email protected]
Jean-Philippe Métivier
Affiliation:
GREYC-CNRS, UMR 6072, Université de Caen, 14032 Caen; [email protected]
Gauthier Quesnel
Affiliation:
INRA, UR 875 Biométrie et Intelligence Artificielle, 31326 Toulouse. [email protected], [email protected], [email protected], [email protected]
Alexandre Joannon
Affiliation:
INRA, UR 980 SAD-Paysage, 35042 Rennes; [email protected]
Frédérick Garcia
Affiliation:
INRA, UR 875 Biométrie et Intelligence Artificielle, 31326 Toulouse. [email protected], [email protected], [email protected], [email protected]
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Abstract

Application tools for the crop allocation problem (CAP) are required for agricultural advisors to design more efficient farming systems. Despite the extensive treatment of this issue by agronomists in the past, few methods tackle the crop allocation problem considering both the spatial and the temporal aspects of the CAP. In this paper, we precisely propose an original formulation addressing the crop allocation planning problem while taking farmers’ management choices into account. These choices are naturally represented by hard and soft constraints in the Weighted CSP formalism. We illustrate our proposition by solving a medium–size virtual farm using either a WCSP solver (toulbar2) or an ILP solver (NumberJack/SCIP). This preliminary work foreshadows the development of a decision–aid tool for supporting farmers in their crop allocation strategies.

Type
Research Article
Copyright
© EDP Sciences, ROADEF, SMAI, 2013

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