A multi-objective optimization algorithm for flow shop group scheduling problem with sequence dependent setup time and worker learning

The optimization of production systems has become increasingly important in manufacturing industries due to the growing competition and market demands. One of the overriding concerns of managers is the efficient exploitation of workers' learning to increase output and decrease downtime. The learning effect symbolizes the improvement of workers' ability and performance through the repetition of similar jobs. On the other hand, it is a critical requirement for decision-makers to have effective management of the transportation phase to achieve an optimal production plan. This paper considers a flow shop sequence-dependent group scheduling problem (FSDGS) with a learning effectto minimize two contradictory objective functions, namely makespan and energy consumption.