Using a genetic algorithm to define worst-best and best-worst options of a DEXi-type model: Application to the MASC model of cropping-system sustainability - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue Computers and Electronics in Agriculture Année : 2013

Using a genetic algorithm to define worst-best and best-worst options of a DEXi-type model: Application to the MASC model of cropping-system sustainability

Résumé

DEXi-type models have been used recently to assess specific problems in agricultural systems and to assess cropping-system scenarios. Finding the set of the ‘‘worst-best’’ (lowest scores for basic attributes that lead to the highest score for the root attribute) and ‘‘best-worst’’ (highest scores for basic attributes that lead to the lowest score for the root attribute) options are of interest for improving current cropping systems. As DEXi-type models revealed a monotonicity property, we used a genetic algorithm to find these two sets. These sets are small and show that only a few attributes need to have low scores to reach the best-worst options or high scores to reach the worst-best options. These attributes are those with ahigh sensitivity index.

Dates et versions

hal-02648539 , version 1 (29-05-2020)

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Citer

Jacques-Eric J.-E. Bergez. Using a genetic algorithm to define worst-best and best-worst options of a DEXi-type model: Application to the MASC model of cropping-system sustainability. Computers and Electronics in Agriculture, 2013, 90, pp.93-98. ⟨10.1016/j.compag.2012.08.010⟩. ⟨hal-02648539⟩
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