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A genetic-algorithm-based optimization model for scheduling flexible assembly lines

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Abstract

In this paper, a scheduling problem in the flexible assembly line (FAL) is investigated. The mathematical model for this problem is presented with the objectives of minimizing the weighted sum of tardiness and earliness penalties and balancing the production flow of the FAL, which considers flexible operation assignments. A bi-level genetic algorithm is developed to solve the scheduling problem. In this algorithm, a new chromosome representation is presented to tackle the operation assignment by assigning one operation to multiple machines as well as assigning multiple operations to one machine. Furthermore, a heuristic initialization process and modified genetic operators are proposed. The proposed optimization algorithm is validated using two sets of real production data. Experimental results demonstrate that the proposed optimization model can solve the scheduling problem effectively.

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Authors and Affiliations

  1. Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong

    Z. X. Guo, W. K. Wong, S. Y. S. Leung, J. T. Fan & S. F. Chan

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  1. Z. X. Guo
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  2. W. K. Wong
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  3. S. Y. S. Leung
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  4. J. T. Fan
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  5. S. F. Chan
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Correspondence to Z. X. Guo.

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Guo, Z.X., Wong, W.K., Leung, S.Y.S. et al. A genetic-algorithm-based optimization model for scheduling flexible assembly lines. Int J Adv Manuf Technol 36, 156–168 (2008). https://doi.org/10.1007/s00170-006-0818-6

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  • DOI: https://doi.org/10.1007/s00170-006-0818-6

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