AIAug 20, 2025

Argumentation for Explainable Workforce Optimisation (with Appendix)

arXiv:2508.15118v2h-index: 4ECAI
Originality Synthesis-oriented
AI Analysis

This addresses the need for explainable optimization in workforce management for industrial applications, though it appears incremental by applying existing argumentation methods to a new domain.

The paper tackles the problem of workforce management by optimizing makespan and travel distance for a team of operators, and shows that using abstract argumentation provides faithful explanations and leads to faster and more accurate problem-solving in a user study.

Workforce management is a complex problem involving the optimisation of the makespan and travel distance required for a team of operators to complete a set of jobs, using a set of instruments. A crucial challenge in workforce management is accommodating changes at execution time so that explanations are provided to all stakeholders involved. Here, we show that, by understanding workforce management as abstract argumentation in an industrial application, we can accommodate change and obtain faithful explanations. We show, with a user study, that our tool and explanations lead to faster and more accurate problem solving than conventional manual approaches.

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