- Ementa
- The subject aims to contribute to the training of students in the Production Engineering Program by providing theories and techniques to support decision-making applied to Production Engineering based on non-classical logic. Students are expected to gain an understanding of the decision-making process in various topics, such as supply chain management, logistics, expert systems, intelligent computing, automation and robotics. Group decision techniques based on fuzzy theory have been proposed in the literature to support imprecise evaluation and aggregate the opinions of different experts. Furthermore, disagreement between experts can naturally arise depending on the complexity and nature of the problem. To this end, we rely on paraconsistent logic that can mechanically handle conflicting or imprecise data. Group decision-making is more representative of the organization’s view of the problem than individual decision-making, favoring a more systemic view.
- Bibliografia
- Abe, J. M., Akama, S., & Nakamatsu, K. (2015). Introduction to annotated logics: foundations for paracomplete and paraconsistent reasoning (Vol. 88). Springer.
- Akama, S. (Ed.). (2016). Towards Paraconsistent Engineering (Vol. 110). Cham: Springer International Publishing.
- Cox, C. O. (2021). Decision Making in Risk Management: Quantifying Intangible Risk Factors in Projects. CRC Press. https://doi.org/10.1201/9781003168409.
- Da Silva Filho, J. I., Torres, G. L., & Abe, J. M. (2010). Uncertainty treatment using paraconsistent logic: introducing paraconsistent artificial neural networks (Vol. 211). Ios Press. doi: 10.3233/978-1-60750-558-7-I.
- De Carvalho, F. R., & Abe, J. M. (2018). A paraconsistent decision-making method (Vol. 87). Springer. https://doi.org/10.1007/978-3-319-74110-9.
- Jair Minoro Abe, Paraconsistent Intelligent Based-Systems: New Trends in the Applications of Paraconsistency, editor, Book Series: “Intelligent Systems Reference Library”, Springer-Verlag, Vol. 94, ISBN:978-3-319-19721-0, 306 pages, Germany, 2015.
- Abe, J. M. (Ed.). (2015). Paraconsistent intelligent-based systems: New trends in the applications of paraconsistency (Vol. 94). Springer. https://doi.org/10.1007/978-3-319-19722-7.
- Driscoll, P. J., Parnell, G. S., & Henderson, D. L. (Eds.). (2022). Decision making in systems engineering and management. John Wiley & Sons.
- Jain, P., Abhishek, K., & Chatterjee, P. (Eds.). (2024). Decision-making Models and Applications in Manufacturing Environments. CRC Press. ISBN 9781774913550.