A multi-objective approach based on soft computing techniques for production scheduling in Corrugator manufacturing plants

Abstract

Abstract
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.