@inproceedings{fdi:010094536,
  title = {{S}upporting sustainable agroecological initiatives for small farmers through constraint programming},
  author = {{C}halland, {M}. and {V}ismara, {P}. and {J}usteau-{A}llaire, {D}imitri and {T}ourdonnet {D}e, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{M}eeting the {UN}'s objective of developing sustainable agriculture requires, in particular, accompanying small farms in their agroecological transition. {T}his transition often requires making the agrosystem more complex and increasing the number of crops to increase biodiversity and ecosystem services. {T}his paper introduces a flexible model based on {C}onstraint {P}rogramming ({CP}) to address the crop allocation problem. {T}his problem takes a cropping calendar as input and aims at allocating crops to respect several constraints.  {W}e have shown that it is possible to model both agroecological and operational constraints at the level of a small farm. {E}xperiments on an organic micro-farm have shown that it is possible to combine these constraints to design very different cropping scenarios and that our approach can apply to real situations. {O}ur promising results in this case study also demonstrate the potential of {AI}-based tools to address small farmers' challenges in the context of the sustainable agriculture transition.},
  keywords = {},
  numero = {},
  pages = {5924--5931},
  booktitle = {{P}roceedings of the {T}hirty-{S}econd {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence ({IJCAI}-23)},
  year = {2023},
  DOI = {10.24963/ijcai.2023/657},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094536},
}