Integrating preferences within multiobjective flexible job shop scheduling

When faced with a multiobjective optimization problem, it is necessary to consider the decision-maker preferences in order propose best compromise solution. We flexible job shop scheduling problem and that represented using non-compensatory reference level-based preference model. show how integrating this model into genetic algorithm allows obtain solutions surpass more aspiration levels when compared classical approaches. Furthermore, these are found faster greater numbers which facilitates their integration within workshop.