Abstract
Kanban system plays an important role in many manufacturing systems. The design of a Kanban system addresses the selection of two important parameters, i.e., the number of Kanbans and the lot size. This problem has been tackled in a number of studies using simulation models. But in the absence of an efficient gradient analysis method of the objective function, it is time-consuming in solving large-scale problems using a simulation model coupled with a meta-heuristic algorithm. In this chapter, a gradient-based heuristic is applied to a genetic algorithm for the design of a multi-product Kanban system. Several case studies in different sizes have been tried out and solutions from the modified genetic algorithm were compared to those from the classical genetic algorithm. Notable improvements in computing times or solutions by the modified genetic algorithm can be observed.
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
References
Kumar CS, Panneerselvam R (2007) Literature review of JIT-KANBAN system. Int J Adv Manuf Technol 32:393–408
Yoichi S, Naoto H (1999) Transient behavior of single stagekanban system based on the queuing model. Int J Prod Econ 60&61:369–374
Nori VS, Sarker BR (1998) Optimum number of kanbans between two adjacent stations. Prod Plan Control 9:60–65
Berkley BJ (1996) A simulation study of container size in two-card kanban system. Int J Prod Res 34:3417–3445
Shahabudee P, Krishnaiah K (1999) Design of a bi-criteria kanban system using genetic algorithm. Int J Manage Syst 15:257–274
Shahabudee P, Krishnaiah K, Narayanan MT (1999) Design of a two-card dynamic kanban system using a simulated annealing algorithm. Int J Adv Manuf Technol 21:754–759
Huang L, Gao Y, Qian F, Tang SZ et al (2010) Design of a multi-product kanban system based on bottleneck analysis. In: The 2nd international conference on computer and automation engineering, vol 25, pp 80–83
Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan, Ann Arbor, vol 25, pp 156–157
Roser C, Nakano M, Tanaka M (2002) Shifting bottleneck detection. In: Proceedings of the 2002 winter simulation conference, vol 846, pp 1079–1086
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this paper
Cite this paper
Huang, L. (2013). Multi-Product Kanban System Based on Modified Genetic Algorithm. In: Zhong, Z. (eds) Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012. Lecture Notes in Electrical Engineering, vol 219. Springer, London. https://doi.org/10.1007/978-1-4471-4853-1_100
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4853-1_100
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4852-4
Online ISBN: 978-1-4471-4853-1
eBook Packages: EngineeringEngineering (R0)