Trustworthy and Explainable Decision-Making for Workforce allocation
December 13, 2024 Β· Declared Dead Β· π arXiv.org
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Authors
Guillaume Povéda, Ryma Boumazouza, Andreas Strahl, Mark Hall, Santiago Quintana-Amate, Nahum Alvarez, Ignace Bleukx, Dimos Tsouros, Hélène Verhaeghe, Tias Guns
arXiv ID
2412.10272
Category
cs.AI: Artificial Intelligence
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In industrial contexts, effective workforce allocation is crucial for operational efficiency. This paper presents an ongoing project focused on developing a decision-making tool designed for workforce allocation, emphasising the explainability to enhance its trustworthiness. Our objective is to create a system that not only optimises the allocation of teams to scheduled tasks but also provides clear, understandable explanations for its decisions, particularly in cases where the problem is infeasible. By incorporating human-in-the-loop mechanisms, the tool aims to enhance user trust and facilitate interactive conflict resolution. We implemented our approach on a prototype tool/digital demonstrator intended to be evaluated on a real industrial scenario both in terms of performance and user acceptability.
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