4th International Conference on Intelligent and Fuzzy Systems (INFUS), Bornova, Turkey, 19 - 21 July 2022, vol.504, pp.941-956
COVID-19 outbreak has damaged the global supply chains, it has affected both goods and service provider supply chains unprecedentedly. Post COVID-19 era is full of uncertainty based on many changes that have happened. Some new parameters are introduced because of the outbreak and bring out new circumstances. These new challenges consequently will increase the ambiguity around the supply chain networks. This study is designed to investigate and evaluate the ambiguity of supply chain networks in the post-COVID-19 era, to strengthen and increase the resilience of SCN systems. The challenges are clustered into different patterns and for each pattern, many strategy approaches are introduced in the literature part. But not only those are not useful without understanding challenges specifically for each SCN but also, it is not possible to apply all of those strategy solutions. This study aims to first understand the challenges and effects of each disruption pattern specifically for each SCN and then select in a more detailed way the most appropriate strategy. To catch the goal of evaluating the resilience of supply chain networks, some significant challenges are identified based on the literature part. An algorithm consists of three stages, first define the uncertainty, second pattern recognition of disruption patterns, and third strategy selection to increase SCN resilience is proposed based IVq-ROFSs Hamacher Aggregation operators and Dice similarity measures. An illustrative example of the SCN resilience problem is evaluated by the proposed algorithm under the Interval Valued q-Rung Ortho Pair Fuzzy structure to show the applicability and reliability of the proposed method. Finally, this paper provides guidelines and strategies for increasing the resilience of supply chain networks in the post-COVID-19 outbreak.