Online cutting stock optimization with prioritized orders

Abstract

PurposeTo have all the required components of batches of product orders ready for timely assembly and delivery, the real time wood strip cutting patterns in a major solid wood furniture manufacturing plant has to be dynamically generated based on both the order priority and the minimum wood waste.Design/methodology/approachAn adaptive fuzzy ranking method and a recursive function for pattern generation were integrated into an optimization procedure to solve the real time one‐dimensional multiple‐grade cutting stock problem when orders are prioritized.FindingsThe simulation results illustrate that the optimization algorithm produce considerably less waste than the current approach. If implemented in the industry, the saving in raw material could be in the range of 5‐10 percent.Research limitations/implicationsThe optimization algorithm is for the cut‐to‐size decisions only with the consideration of the order priorities. The overall scheduling of the production shop floor is not addressed.Practical implicationsThe algorithm can be used on the cutting machines as an online patterns generator and cutting optimizer.Originality/valueThere is no literature available for the real time one‐dimensional multiple‐grade cutting stock problem when orders are prioritized. The few commercial optimizers have unknown algorithms with unpredictable waste.