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Genetic Algorithm for Concurrent Balancing of Mixed-Model Assembly Lines with Original Task Times of Models
Department of Mechanical Engineering, Rajalakshmi Engineering College, Anna University, Chennai, India
Department of Industrial Engineering, College of Engineering, Anna University, Chennai, India
- 1 Department of Mechanical Engineering, Rajalakshmi Engineering College, Anna University, Chennai, India
- 2 Department of Industrial Engineering, College of Engineering, Anna University, Chennai, India
Intelligent Information Management·Volume 05 (2013)·Pages 84–92·Published 24 May 2013·DOI10.4236/iim.2013.53009
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Abstract
The growing global competition compels manufacturing organizations to engage themselves in all productivity impro vement activities. In this direction, the consideration of mixed-model assembly line balancing problem and implement ing in industries play s 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 ori ginnal 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.
KeywordsAssembly Line BalancingCycle TimeGenetic AlgorithmCrossover OperationMixed-Model
- 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.
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- R. Panneerselvam, “Production and Operations Management,” 3rd Edition, PHI Learning Private Limited, New Delhi, 2012.
- 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
- 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.