2687. Well-being-aware Dual-resource-constrained flexible job shop scheduling problem
Invited abstract in session TD-12: Job shop scheduling, stream Scheduling and Project Management.
Tuesday, 14:30-16:00Room: Clarendon SR 1.02
Authors (first author is the speaker)
| 1. | Peyman Yasari
|
| Industrial Systems Engineering and Product Design, Ghent University | |
| 2. | Dieter Claeys
|
| Industrial Systems Engineering and Product Design, Ghent University | |
| 3. | El-Houssaine Aghezzaf
|
| Industrial Management, Ghent University |
Abstract
Nowadays, the importance of well-being in the work environment is undeniable. A lack of physical well-being leads to musculoskeletal disorders, while a lack of mental well-being contributes to worker burnout. Both issues result in significant losses of time, cost, and energy for industries. Although the primary phase for addressing these aspects is during task and workstation design, it is also possible to manage resources to balance and adjust workloads during the exploitation phase. Well-being-aware task allocation and scheduling aims to address this gap.
To achieve this, a mixed-integer linear programming (MILP) model has been developed. This model limits the experienced aggregated task loads to an operator-specific threshold. However, aggregating task loads poses a significant challenge: for physical loads, only a few validated methods exist, which makes the model non-linear for most risk factors, while for cognitive loads, no established method is available. Nevertheless, the proposed model is flexible and can accommodate different measures that provide this feature. An exact solution method is introduced to address the complexity added by the threshold constraints. Additionally, the presentation will discuss a simplified version of the problem that forms the basis for developing a more efficient solution method.
Keywords
- Scheduling
- Optimization Modeling
- Health Care
Status: accepted
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