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