Abstract
To seek the optimal analysis of line balancing in mix-model assembly line, Author comes up with one new enhanced Genetic Algorithm which takes some new engineering constraints into consideration as well as introducing SA factor to avoid premature. Through applying analysis on one real use case, it proves good result of optimization efficiency and quality.
Keywords
References
Cao, Z., Zhu, Y., Zhao, M., et al.: Optimal research on balancing and sequencing of mixed model assembly lines. Information and Control 33(6), 660–664 (2004) (in Chinese)
Yu, Z., Su, P.: Combining genetic algorithm and simulation analysis for mix-model assembly line balancing problem. Computer Integrated Manufacturing Systems 14(6) (June 2008) (in Chinese)
Ling, W.: Research on balancing of mix-model assembly line workstations based on genetic algorithm. Journal of Hefei University of Technology 31(8) (August 2008) (in Chinese)
Cai, M., Wang, F., Yang, S.: Material supply on car assembly line with JIT manufacturing style. Manufacturing Automation 28 (December 2006) (in Chinese)
Modeling of ALB Problem and its optimization. Journal System Simulation 5(11) (October 1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag GmbH Berlin Heidelberg
About this chapter
Cite this chapter
Li, X., Dong, S. (2012). Analysis of Mix-Model Assembly Line Balancing with Enhanced Genetic Algorithm. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25766-7_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-25766-7_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25765-0
Online ISBN: 978-3-642-25766-7
eBook Packages: EngineeringEngineering (R0)