Scheduling mixed-model assembly lines with genetic algorithms: the Aprilia case study

The two authors deal with the topic of the final assembly scheduling realized by the use of Genetic Algorithms (GAs). The objective of the research was to study in depth the use of GA for scheduling mixed-model assembly lines and to propose a model able to produce feasible solutions according to the particular requirements of an important Italian motorbike company, the Aprilia group, as well as to capture the results of this change in terms of better operational performances. In the Aprilia case study, the scheduling problem is made more complex by the “chessboard shifting” of work teams. Therefore, a complex model for scheduling mixed-model assembly lines is required. An application of the GAs is proposed in order to test their effectiveness and robustness. The short elaboration time and the robustness of the final assembly plans, obtained during the test-stage, confirm that the choice was right and suggest the use of GAs in other complex manufacturing systems.