Abstract
We present a sequencing problem given on JIT (Just In Time) manufacturing environments, with the objective of minimizing the variation of manufacturing rates (ORV: Output Rate Variation). Specifically, we propose an extension based on requiring to the sequences the preservation of the production mix throughout the products manufacturing. To solve the ORV and the extended problem, we propose algorithms based on BDP (Bounded Dynamic Programming) and we perform two computational experiments based on instances from the literature.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Boysen, N., Fliedner, M., Scholl, A.: Sequencing mixed-model assembly lines: survey, classification and model critique. European Journal of Operational Research 192(2), 349–373 (2009)
Monden, Y.: Toyota Production System. Industrial Engineering and Management Press, Norcross (1983)
Miltenburg, J.: Scheduling Mixed-Model Assembly Lines for Just-In-Time Production Systems. Management Science 35(2), 192–207 (1989)
Bautista, J., Companys, R., Corominas, A.: Heuristics and exact algorithms for solving the Monden problem. European Journal of Operational Research 88(1), 101–113 (1996)
Kubiak, W.: Minimizing variation of production rates in just-in-time systems: A survey. European Journal of Operational Research 66(3), 259–271 (1993)
Jin, M., Wu, S.D.: A new heuristic method for mixed model assembly line balancing problem. Computers & Industrial Engineering 44(5), 159–169 (2002)
Miltenburg, J.: Level schedules for mixed-model JIT production lines: characteristics of the largest instances that can be solved optimally. International Journal of Production Research 45(16), 3555–3577 (2007)
Bautista, J., Cano, A.: Solving mixed model sequencing problem in assembly lines with serial workstations with work overload minimisation and interruption rules. European Journal of Operational Research 210(3), 495–513 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bautista, J., Cano, A., Alfaro, R., Batalla, C. (2013). Impact of the Production Mix Preservation on the ORV Problem. In: Bielza, C., et al. Advances in Artificial Intelligence. CAEPIA 2013. Lecture Notes in Computer Science(), vol 8109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40643-0_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-40643-0_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40642-3
Online ISBN: 978-3-642-40643-0
eBook Packages: Computer ScienceComputer Science (R0)