Abstract
The main objective of this paper is to improve the performance measures of a multi-objective mixed model assembly line. The motivation of our work is from the paper by Zhang and Gen [1] in which the assembly line problem is solved by using genetic algorithm. Mathematical solutions of their work show balance efficiency (E b) of 86.06 percent, cycle time (C T) of 54 minutes, work content (T wc) is 185.8 minute, production rate (R p) is 1.11E, where E is line efficiency. When the same mathematical model is reconstructed by changing decision variables (changing variables that hold the relationship between the task-station-models to task-worker-model) without changing the meaning of constraints and solved using the branch and bound (B&B) method using Lingo 10 software, there is a significant improvement in performance factors of assembly line. The mathematical solutions are obtained as follows. The balance efficiency (E b) increases by 3.86 percent, cycle time (C T) decreases by 25.55 percent, work content (T wc) decrease by 22.17 percent and production rate (R p) decease by 34.23 percent.
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© 2015 Springer International Publishing Switzerland
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Choudhary, S., Agrawal, S. (2015). Multiobjective Mixed Model Assembly Line Balancing Problem. In: El-Alfy, ES., Thampi, S., Takagi, H., Piramuthu, S., Hanne, T. (eds) Advances in Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-319-11218-3_58
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DOI: https://doi.org/10.1007/978-3-319-11218-3_58
Publisher Name: Springer, Cham
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