Risk factor assessment in agricultural supply chain by fuzzy logic

Abstract

Abstract Significant uncertainty characterizes the harvest period. This aspect is due to various risks impacting agrifood supply chains. The occurrence of risks is due to hazards: technological failures, technical breakdowns, or adverse weather conditions. Hence, the operational time of the agricultural supply chain during the harvest period increases due to such risk factors. In essence, some hazards are fuzzy, and the nature of most threats is characterized by significant uncertainty. Classical risk assessment methods do not allow assessing simultaneously the impact of various risks, especially those expressed fuzzy (weather conditions). Therefore, the study objective is to design a fuzzy model assessing risk factors that impact the increase in the operating time of the agrifood supply chain during the harvest period. As initial parameters in the indistinct model, three groups of risk factors were accepted: weather conditions, technological failures and technical malfunctions. The MATLAB Fuzzy Toolbox is used to design the fuzzy model, and the model architecture is implemented in Simulink. The modelling results can be used to create the necessary reserves of the harvesting and transport complex to ensure timely harvesting and reduce the negative impact of hazards on the agricultural supply chain operating.