Scheduling mixed-model production on multiple assembly lines with shared resources using genetic algorithms: the case study of a motorbike company

The 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 also according to the particular requirements of an important Italian motorbike company, as well as to capture the results of this change in terms of better operational performances. The “chessboard shifting” of work teams among the mixed-model assembly lines of the selected company makes the scheduling problem more complex. Therefore, a complex model for scheduling is required. We propose an application of the GAs in order to test their effectiveness to real scheduling problems. The high quality of the final assembly plans with a high adherence to the delivery date, obtained in a short elaboration time, confirms that the choice was right and suggest the use of GAs in other complex manufacturing systems.