Scheduling jobs in an Alcan aluminium foundry using a genetic algorithm

Abstract

We present a genetic algorithm for the solution of an industrial scheduling problem in an Alcan aluminium foundry situated in Québec. We seek the best processing sequence for n orders on a m parallel machines. The set-up times are sequence dependent and we must deal with multiple criteria. There are also a number of structural constraints that distinguish this situation from the classical model. The performance of the solution approach is compared with the results of the scheduling process used by the firm according to three criteria: meeting due dates, number and duration of required set-ups and metal flow.