Table of Contents
Advances in Decision Sciences
Volume 2014, Article ID 874031, 11 pages
Research Article

Scheduling Mixed-Model Production on Multiple Assembly Lines with Shared Resources Using Genetic Algorithms: The Case Study of a Motorbike Company

1Department of Mechanical and Aerospace Engineering, University of Rome “La Sapienza”, Via Eudossiana 18, 00184 Rome, Italy
2Department of Electrical, Management and Mechanical Engineering, University of Udine, Via Delle Scienze 206, 33100 Udine, Italy
3Department of Computer, Control and Management Engineering “Antonio Ruberti”, University of Rome “La Sapienza”, Via Ariosto 25, 00186 Rome, Italy

Received 27 May 2014; Accepted 15 September 2014; Published 2 October 2014

Academic Editor: Roger Z. Ríos-Mercado

Copyright © 2014 Francesco Costantino et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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 high adherence to the delivery date, obtained in a short elaboration time, confirms that the choice was right and suggests the use of GAs in other complex manufacturing systems.