Back
 IIM  Vol.5 No.3 , May 2013
Genetic Algorithm for Concurrent Balancing of Mixed-Model Assembly Lines with Original Task Times of Models
Abstract: The growing global competition compels manufacturing organizations to engage themselves in all productivity improvement activities. In this direction, the consideration of mixed-model assembly line balancing problem and implementing in industries plays a major role in improving organizational productivity. In this paper, the mixed model assembly line balancing problem with deterministic task times is considered. The authors made an attempt to develop a genetic algorithm for realistic design of the mixed-model assembly line balancing problem. The design is made using the originnal task times of the models, which is a realistic approach. Then, it is compared with the generally perceived design of the mixed-model assembly line balancing problem.
Cite this paper: P. Sivasankaran and P. Shahabudeen, "Genetic Algorithm for Concurrent Balancing of Mixed-Model Assembly Lines with Original Task Times of Models," Intelligent Information Management, Vol. 5 No. 3, 2013, pp. 84-92. doi: 10.4236/iim.2013.53009.
References

[1]   Y. Bai, H. Zhao and L. Zhu, “Mixed-Model Assembly Line Balancing Using the Hybrid Genetic Algorithm,” International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, 11-12 April 2009, pp. 242-245.

[2]   S. Bock, “Using Distributed Search Methods for Balancing Mixed-Model Assembly Lines in the Automotive Industry,” OR Spectrum, Vol. 30, No. 3, 2008, pp. 551-578. doi:10.1007/s00291-006-0069-9

[3]   Y. Bukchin and I. Rabinowitch, “A Branch-and-Bound Based Solution Approach for the Mixed-Model Assembly Line-Balancing Problem for Minimizing Stations and Task Duplication Costs,” European Journal of Operational Research, 174, No. 1, 2006, pp. 492-508. doi:10.1016/j.ejor.2005.01.055

[4]   H. Gokcen and E. Erel, “Binary Integer Formulation for Mixed-Model Assembly Line Balancing Problem,” Computers & Industrial Engineering, Vol. 34, No. 2, 1998, pp. 451-461. doi:10.1016/S0360-8352(97)00142-3

[5]   M.-Z. Jin and S. D. Wu, “A New Heuristic Method for Mixed-Model Assembly Line Balancing Problem,” Computers & Industrial Engineering, Vol. 44, No. 1, 2002, pp. 159-169. doi:10.1016/S0360-8352(02)00190-0

[6]   Y. K. Kim and J. Y. Kim, “A Co-Evolutionary Algorithm for Balancing and Sequencing in Mixed-Model Assembly Lines,” Applied Intelligence, Vol. 13, No. 3, 2000, pp. 247-258. doi:10.1023/A:1026568011013

[7]   S. Matanachai and C. A. Yano, “Balancing Mixed-Model Assembly Lines to Reduce Work Overload,” IIE Transactions, Vol. 33, No. 1, 2001, pp. 29-42. doi:10.1080/07408170108936804

[8]   A. N. Ha, J. Jayaprakash and K. Rengarajan, “A Hybrid Genetic Algorithm Approach to Mixed-Model Assembly Line Balancing,” International Journal of Advanced Manufacturing Technology, Vol. 28, No. 3-4, 2006, pp. 337-341. doi:10.1007/s00170-004-2373-3

[9]   U. Ozcan, H. Cercioglu, H. Gokcen and B. Toklu, “Balancing and Sequencing of Parallel Mixed-Model Assembly Lines,” International Journal of Production Research, Vol. 48, No. 17, 2010, pp. 5089-5113. doi:10.1080/00207540903055735

[10]   R. Panneerselvam, “Production and Operations Management,” 3rd Edition, PHI Learning Private Limited, New Delhi, 2012.

[11]   P. Senthilkumar and P. Shahabudeen, “GA Based Heuristic for the Open Shop Scheduling Problem,” International Journal of Advanced Manufacturing Technology, Vol. 30, No. 3-4, 2006, pp. 297-301. doi:10.1007/s00170-005-0057-2

[12]   P. Su and Y. Lu, “Combining Genetic Algorithm and Simulation for the Mixed-Model Assembly Line Balancing Problem,” 3rd International Conference on Natural Computation (ICNC 2007), Vol. 4, Haikou, 24-27 August 2007, pp. 314-318.

[13]   X. M. Zhang and X. C. Han, “The Balance Problem Solving of the Car Mixed-Model Assembly Line Based on Hybrid Differential Evolution Algorithm,” Applied Mechanics and Materials, Vol. 220-223, 2012, pp. 178-183. doi:10.4028/www.scientific.net/AMM.220-223.178

 
 
Top