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

• A method for uncertainty minimisation in rural planning was implemented.
• Fuzzy Cognitive Maps, Dempster–Shafer theory and optimisation algorithm were merged.
• The DSS was applied to plan policies to cope with economic crisis in a rural system.
• Complexity of examined systems can be analysed and assessed by the model.

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.