An integrated machine scheduling and personnel allocation problem for large-scale industrial facilities using a rolling horizon framework

In this study we present an optimization problem where machine scheduling and personnel allocation decisions are solved simultaneously. The machine scheduling consists of solving a variant of the job shop problem where jobs are allocated in batches and multitasking is allowed. On the other hand, the personnel allocation problem searches for the optimal allocation of human resources to support the facility operation. Although these problems have been extensively studied independently in the literature, the integrated problem has very limited studies, in particular for large-scale industrial environments. We introduce a mathematical formulation for this problem and propose a solution method to evaluate optimal solutions more efficiently. We also implement a rolling horizon framework to test our approach using real-world based instances extracted from an analytical service facility. The results show that, overall improvements of up to 11.6% are achieved compared to the case where no personnel allocation decisions are considered within the scheduling problem.

Automated summary

This study successfully addressed machine scheduling and personnel allocation problems simultaneously, proposing a mathematical formulation and solution method to evaluate optimal solutions more efficiently. The results showed overall improvements of up to 11.6% compared to previous cases without considering personnel allocation decisions within the scheduling problem.