Hybrid heuristics for planning job rotation schedules in assembly lines with heterogeneous workers

Abstract

We investigate the problem of balancing assembly lines with heterogeneous workers while considering job rotation schedules. This problem typically occurs in assembly lines in sheltered work centers for disabled. We propose a hybrid algorithm that uses a Mixed Integer Programming (MIP) to select appropriate schedules from a pool of heuristically constructed solutions. A local search based on MIP neighborhoods is used as a post-optimization method. Our results show that this approach is fast, flexible and accurate when compared with current available methods.