Fuzzy-Multiple Methodology for Assessing the Sustainability of Agricultural Production in the Regions of the Region and their Ranking

We have presented a model for assessing the sustainability of agricultural production based on the aggregation of many significant indicators. The model is based on the use of fuzzy-logical inference systems—fuzzy five-level [0,1]—classifiers used by Nedosekin to assess the state of economic systems, including the risk of bankruptcy of an enterprise. To assess the sustainability of agriculture in each of the districts of the agricultural region, we propose to aggregate the assessments of its three subsystems: economic, social and environmental. We construct each of the estimates of the subsystems by aggregating the normalized values of significant indicators selected in accordance with generally accepted assessment methods. The fuzzy multiple method proposed by us has such advantages over existing analogues as universality, taking into account the significance of indicators by varying the weight coefficients. The methodology was tested by statistical data on the indicators of the Rostov region, taken from Federal State Statistic Service of Russia. It has been established that all districts of the Rostov region can be attributed to the term “development close to sustainable”, and the last two districts can equally well be attributed to the fifth term “high level of sustainability”.