A GRASP for simultaneously assigning and sequencing product families on flexible assembly lines

This paper introduces a new model and solution methodology for a real‐world production scheduling problem arising in the electronics industry. The production environment is a high volume, just‐in‐time, make‐to‐order facility with volatile demand over many product families that are assembled on flexible lines. A distinguishing characteristic of the problem is the presence of non‐traditional sequence‐dependant setup costs, which complicate our ability to find high‐quality solutions. The scheduling problem arose when product variety exceeded the mix that the existing lines could accommodate. A nonlinear integer programming formulation is presented for the problem of minimizing setup costs, and a greedy randomized adaptive search procedure (GRASP) is developed to find solutions. To select the GRASP parameter values, an efficient, space‐filling experimental design method is used based on nearly orthogonal Latin hypercubes. The proposed methodology is tested on actual factory data and compared to a prior heuristic presented in the literature; our heuristic provides a cost savings in 7 out of the 10 cases examined, and an average improvement of 17.39 % which is shown to be highly statistically significant. This improvement is due in part to the introduction of a pre‐processing step to determine preferential and non‐preferential line assignment information.