This paper investigates the feasibility of using fuzzy logic for reshoring decision-making. To achieve this a fuzzy logic system for reshoring decision-making was implemented. The system was configured in two different ways to cover the two main fuzzy logic modeling approaches and sixteen fuzzy inference settings were used in each configuration. The research shows that fuzzy logic is a feasible method for reshoring decision-making. The reduced rule base configuration was more accurate than the complete rule base configuration. However, the reduced rule base also generated more conflicts in particular settings. Among all the fuzzy inference settings used in this research, one of the settings outperformed the others. With regard to the particular inference methods, the research show that maximum is the preferred aggregation method while middle of maximum is the preferred defuzzification method.

@inproceedings{oscm-2019-493,
  title={Fuzzy Logic in a Reshoring Decision-Making Context},
  year={2019},
  author={Per Hilletofth and Movin Sequeira},
  booktitle={Proceedings of the 9th International Conference on Operations and Supply Chain Management, Vietnam, 2019},
  doi={10.31387/oscm410010}
}

Per Hilletofth, Movin Sequeira (2019). Fuzzy Logic in a Reshoring Decision-Making Context. In Proceedings of the 9th International Conference on Operations and Supply Chain Management, Vietnam, 2019. https://doi.org/10.31387/oscm410010