Working Paper Reducing ergonomic risks at mixed-model assembly lines by job rotation scheduling

The proverb “a change is as good as a rest” expresses one of the main advantages of job rotation. In this article, we examine ways to set-up effective job rotation schedules that balance ergonomic risks among workers in mixed-model assembly lines. We show that the problem is NP-hard in the strong sense. Therefore, the development of specialized solution methods is important. Exploiting the problem structure, we propose a fast and effective smoothing heuristic which can be integrated into solution methods for computing initial solutions and/or as a local re-optimization procedure. We find that integrating the smoothing heuristic into a suited tabu search approach is particularly recommendable. In computational experiments, this combination of approaches is able to solve almost all instances of a practical data set in very short computation times of some seconds, whereas the standard solver FICO Xpress and the best-known heuristic from literature perform considerably worse concerning computation time and solution quality.