AbstractThe corrugator scheduling problem is a difficult problem due to a wide varietyof parameters and optimisation objectives that have to be accounted for andthe relationships among them. Majority of solution techniques proposed so faronly deal with minimizing either, the trim waste or pattern changes, this paperproposes a multi-objective evolutionary algorithm to optimize the WPL objective(weighted planning level) and the cost objectives. Computational experimentswere conducted and results were compared against the current shop schedulingmethod used at a real-life corrugator manufacturing facility. A series of experimentswere also conducted to determine the evolutionary algorithm parameters. Theimprovement on performance metrics encourages us to actually implement thealgorithm at the factory.The corrugator scheduling problem is a difficult problem due to a wide varietyof parameters and optimisation objectives that have to be accounted for andthe relationships among them. Majority of solution techniques proposed so faronly deal with minimizing either, the trim waste or pattern changes, this paperproposes a multi-objective evolutionary algorithm to optimize the WPL objective(weighted planning level) and the cost objectives. Computational experimentswere conducted and results were compared against the current shop schedulingmethod used at a real-life corrugator manufacturing facility. A series of experimentswere also conducted to determine the evolutionary algorithm parameters. Theimprovement on performance metrics encourages us to actually implement thealgorithm at the factory.