Multi-Mode Assembly Line Balancing with Multi-Skilled and Traveling Workers

Abstract

The assembly of complex products frequently necessitates workers with different skill profiles. Those workers could be human or robot workers, and may be suited to conduct a single or multiple types of tasks, grouped by skill sets. However, due to high labor cost and low availability, business owners face challenges in selecting and allocating workload to workers. We propose a solution that balances assembly lines while allowing workers to travel among stations to address aforementioned issues. We establish a novel mixed integer programming (MIP) optimization model with the objective of minimizing worker and station costs. In addition, we employ a constructive heuristic and a neighborhood search method to accelerate the solving process for large-scale problems. Lastly, through experiments inspired by a real-world case study, we distill some insights regarding the application of traveling workers in such assembly environments.