This paper presents a decision-support system for reshoring decision-making based on fuzzy logic. The construction and functionality of the decision-support system is briefly outlined and evaluated in a high-cost environment contemplating six specific decision criteria, namely cost, quality, time, flexibility, innovation and sustainability. A major challenge with fuzzy logic solutions has to do with the construction of the fuzzy inference rules. In the relocation domain, the fuzzy inference rules represent the knowledge and competence of relocation experts and they are usually created manually by the same experts. One obstacle is that the complexity of the fuzzy inference rules increases with the number of decision criteria. To overcome this complexity issue, this paper presents a solution whereby the fuzzy inference rules are automatically generated by applying one hundred reshoring scenarios as input data. The reshoring decision recommendations produced by the fuzzy logic decision-support system are demonstrated to be close to those of human reshoring domain experts.

@inproceedings{oscm-2019-459,
  title={AUTOMATIC GENERATION OF FUZZY INFERENCE RULES IN A RESHORING DECISION CONTEXT},
  year={2019},
  author={Anders Adlemo and Per Hilletofth},
  booktitle={Proceedings of the 9th International Conference on Operations and Supply Chain Management, Vietnam, 2019},
  doi={10.31387/oscm410236}
}

Anders Adlemo, Per Hilletofth (2019). AUTOMATIC GENERATION OF FUZZY INFERENCE RULES IN A RESHORING DECISION CONTEXT. In Proceedings of the 9th International Conference on Operations and Supply Chain Management, Vietnam, 2019. https://doi.org/10.31387/oscm410236