Job-rotation scheduling optimization for a heterogeneous workforce

In the manufacturing industry, humans still play an important role in many processes. It is widely recognized that working can often bring some health risks to workers, both mental and physical. One approach that is commonly used to reduce the risks of negative health effects is to do a job rotation. It can also be challenging to make the most of the workforce that is available. It is also commonly known that every worker has their own unique characteristics, known as heterogeneity. The heterogeneity of humans can cause uncertainty to the productivity. Consideration of the heterogeneity can be beneficial to both the worker and productivity. In this paper, a job-rotation scheduling model will be developed as a binary linear programming model. The model will also bring the heterogeneity of workers into consideration to maintain their health and well-being while maximizing the productivity. Another feature is that the model will equalize the workload among the workforce to avoid an unfair workload. A numerical example is then demonstrated to show the real application of the model, along with tests and model validation. Results, discussion, and analysis are also stated in this paper.