Reducing ergonomic risks by job rotation scheduling

Abstract

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. The practical relevance of the problem is comprehensively discussed on examples from the automobile industry. We present the ergonomic job rotation scheduling problem and show that it 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.