Industry 5.0 involves a transformation towards human-centric and green-aware industrial ecosystems. Sustainable, safe and efficient allocation of process activities to workers is crucial in this context, as excessive workloads can bring detrimental effects on them, potentially causing long-term harm and reducing overall productivity. This paper addresses the problem of reassigning activities to workers, balancing between efficiency and sustainability through a flexible and periodic negotiation process, in which workers can refuse assigned activities if these exceed a sustainable stress level, which is monitored through wearable devices. We model it through Mixed Integer Linear Programming (MILP) with a hierarchical objective function, aimed at first maximizing the number of assignments and then minimizing the cost due to reassignments, levels of stress and possible overtimes. As experiments show, the solution time of our MILP model makes dynamic negotiation feasible in realistic settings.
Personalized Task Reassignment in Industry 5.0: A MILP-Based Solution Approach / Diamantini, Claudia; Pisacane, Ornella; Potena, Domenico; Storti, Emanuele. - 2:(2025), pp. 813-820. (Intervento presentato al convegno 27th International Conference on Enterprise Information Systems tenutosi a Porto, Portugal nel 2025) [10.5220/0013197400003929].
Personalized Task Reassignment in Industry 5.0: A MILP-Based Solution Approach
Diamantini, Claudia;Pisacane, Ornella;Potena, Domenico;Storti, Emanuele
2025-01-01
Abstract
Industry 5.0 involves a transformation towards human-centric and green-aware industrial ecosystems. Sustainable, safe and efficient allocation of process activities to workers is crucial in this context, as excessive workloads can bring detrimental effects on them, potentially causing long-term harm and reducing overall productivity. This paper addresses the problem of reassigning activities to workers, balancing between efficiency and sustainability through a flexible and periodic negotiation process, in which workers can refuse assigned activities if these exceed a sustainable stress level, which is monitored through wearable devices. We model it through Mixed Integer Linear Programming (MILP) with a hierarchical objective function, aimed at first maximizing the number of assignments and then minimizing the cost due to reassignments, levels of stress and possible overtimes. As experiments show, the solution time of our MILP model makes dynamic negotiation feasible in realistic settings.| File | Dimensione | Formato | |
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