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Multi-objective optimization in single-row layout design using a genetic algorithm

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Abstract

This paper presents the development of a genetic algorithm for determining a common linear machine sequence for multi-products with different operation sequences and facilities with a limited number of duplicate machine types available for a job. This work aims to minimize the total flow distance traveled by products, reduce the number of machines arranged in the final linear sequence, and decrease the total investment cost of the machines used in the final sequence. We assume that product flow runs only in the forward direction, either via in-sequence or bypass movement. We demonstrate the effectiveness of the proposed algorithm by solving a typical layout design problem taken from literature, and several randomly generated problems. Results indicate that the proposed algorithm serves as a practical decision support tool for resolving layout problems in manufacturing facilities.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, National Engineering College, K.R. Nagar, Tamilnadu, Kovilpatti, 628 503, India

    N. Lenin & D. Ravindran

  2. Sree Sowdambika College of Engineering, Chettikurichi, Tamilnadu, Aruppukottai, 626 134, India

    M. Siva Kumar

  3. Department of Mechanical Engineering, Curtin University, GPO Box U 1987, Perth, WA, 6845, Australia

    M. N. Islam

Authors
  1. N. Lenin
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  2. M. Siva Kumar
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  3. M. N. Islam
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  4. D. Ravindran
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Corresponding author

Correspondence to M. Siva Kumar.

Appendix

Appendix

Table 14 Operation sequences and product demand of example problems
Full size table
Table 15 Machine types and its duplicates for the example problems
Full size table
Table 16 Machine types and its cost for the example literature problems
Full size table

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Lenin, N., Siva Kumar, M., Islam, M.N. et al. Multi-objective optimization in single-row layout design using a genetic algorithm. Int J Adv Manuf Technol 67, 1777–1790 (2013). https://doi.org/10.1007/s00170-012-4608-z

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  • DOI: https://doi.org/10.1007/s00170-012-4608-z

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