Date | Time: November 22, 2023 | 14h00 – 15h00

Location: Building VIIRoom 1.9

14:00 – 14:15 

Alexandra Tenera, Department of Mechanical and Industrial Engineering, UNIDEMI

Scheduling and Managing Uncertainty from a Theory of Constraints (ToC) Perspective

Abstract: Theory of Constraints (ToC) includes specific concepts, principles, methods, and tools, which are being explored to improve productive systems performance in many well-known organizations from several economic domains. It has been tested and applied in a standalone format or combined with other organizational continuous improvement approaches such as Lean and Six Sigma. This session intends to give a brief overview of some Portuguese ToC exploratory case results, as well as potential challenges for coming developments.

14:15 – 14:30 

Paula Amaral, Department of Mathematics, NOVA MATH

White Box Models

Abstract: Machine learning models have been successfully applied in many situations, often without a critical perspective on these mechanisms. Black box models make it very difficult, if not impossible, to perform counterfactual analysis. Exploring other, more transparent machine learning techniques can be beneficial in situations where scrutinizing the model behind the results is important. In this presentation, we will discuss two perspectives: one based on the analysis of symbolic data and another that introduces a new classification model based on a cloud of spheres.

14:30 – 15:00