Abstract
This paper presents a group scheduling problem for manufacturing cells, in which parts may visit different cells. By addressing intra-cell scheduling, the sequence of parts within manufacturing cells is determined; however, in inter-cell scheduling the sequence of cells is obtained. We design a new mathematical model for a multi-objective group scheduling problem in a cellular manufacturing system (CMS) with respect to bi-objectives minimizing the makespan and intra-cell movement and the tardiness cost. Thus, we develop a meta-heuristic algorithm based on particle swarm optimization (PSO) in order to solve the given problem. The related results confirm the efficiency and the effectiveness of our proposed PSO to provide good solutions, especially for medium and large-sized problems.
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
Lu, L.F., Yuan, J.J.: The Single Machine Batching Problem with Identical Family Setup Times to Minimize Maximum Lateness is Strongly NP-Hard. European Journal of Operational Research 177, 1302–1309 (2007)
Lin, S.-W., Ying, K.-C., Lee, Z.-J.: Meta-heuristics for Scheduling a Non-permutation Flow Line Manufacturing Cell with Sequence Dependent Family Setup Times. Computers & Operations Research 36(4), 1110–1121 (2009)
Hitomi, K., Ham, I.: Operations Scheduling For Group Technology Applications. Annals of the CIRP 25(1), 419–422 (1976)
Tavakkoli-Moghaddam, R., Gholipour-Kanani, Y., Cheraghalizadeh, R.: A Genetic and Memetic Algorithm Approach to Sequencing and Scheduling of Cellular Manufacturing Systems. Int. J. of Management Science and Engineering Management 3(2), 119–130 (2008)
Rahimi-Vahed, A.R., Mirghorbani, S.M., Rabbani, M.: A New Particle Swarm Algorithm for a Multi-objective Mixed-model Assembly Line Sequencing Problem. Soft Computing 11, 997–1012 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tavakkoli-Moghaddam, R., Jafari-Zarandini, Y., Gholipour-Kanani, Y. (2010). Multi-objective Particle Swarm Optimization for Sequencing and Scheduling a Cellular Manufacturing System. In: Huang, DS., McGinnity, M., Heutte, L., Zhang, XP. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Communications in Computer and Information Science, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14831-6_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-14831-6_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14830-9
Online ISBN: 978-3-642-14831-6
eBook Packages: Computer ScienceComputer Science (R0)