Using simulation to improve planning decisions in mixed-model assembly lines

In this paper, we discuss an optimization problem for mixed-model assembly lines in the aerospace industry. We minimize the total inventory and labor costs of an assembly line assuming a given job (airplane) sequence. A variable neighborhood search (VNS) approach is used to determine an appropriate number of workers for each station and processing times for jobs on stations. We are interested in executing the resulting plans in a stochastic simulation model to compute expected objective values in the face of uncertainty. An aggregated simulation model of the assembly line is described. Results of simulation experiments are presented that demonstrate that the proposed simulation-based approach leads to improved planning decisions.