A bi-objective optimization for flow shop group scheduling problem with sequence dependent setup time

The minimization of makespan as an indicator of productivity and service level by using learning effect and high cadences during the production and transportation of products leads to an increase in energy consumption that has a negative effect on the environment and contributes to climate change. A bi-objective mixed integer linear programming model is developed in order to join the two objectives into one using the LP-metric method. Based on a real case study of the flow shop sequence dependent group scheduling problem, several experiments are carried out using different learning rates and varying the weights of the two objective functions in order to support the decision-maker in his operational and tactical choices.