Minimisation of uncertainty in decision-making processes using optimised probabilistic Fuzzy Cognitive Maps: A case study for a rural sector

Several studies have focused on methods of increasing system and uncertainty knowledge for socio-economic and environmental policies; however, the nonlinearity and dynamism of real world increase the gap between uncertainty depiction and its evaluation in policy strategies. This work attempts to implement a methodology that is able to minimise uncertainty in decision support tools related to rural planning and management. Fuzzy Cognitive Maps, the Dempster-Shafer theory and nonlinear optimisation were applied to achieve the above-mentioned goal. The method was tested to describe suitable policies and intervention strategies to address the effects of the recent economic crisis in the agricultural sector.