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A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model

Author

Listed:
  • Xiang Tian
  • Xiyu Liu
  • Hongyan Zhang
  • Minghe Sun
  • Yuzhen Zhao

Abstract

A DNA (DeoxyriboNucleic Acid) algorithm is proposed to solve the job shop scheduling problem. An encoding scheme for the problem is developed and DNA computing operations are proposed for the algorithm. After an initial solution is constructed, all possible solutions are generated. DNA computing operations are then used to find an optimal schedule. The DNA algorithm is proved to have an O(n2) complexity and the length of the final strand of the optimal schedule is within appropriate range. Experiment with 58 benchmark instances show that the proposed DNA algorithm outperforms other comparative heuristics.

Suggested Citation

  • Xiang Tian & Xiyu Liu & Hongyan Zhang & Minghe Sun & Yuzhen Zhao, 2020. "A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-21, December.
    • Handle: RePEc:plo:pone00:0242083
    DOI: 10.1371/journal.pone.0242083
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    References listed on IDEAS

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    1. Erik Winfree & Furong Liu & Lisa A. Wenzler & Nadrian C. Seeman, 1998. "Design and self-assembly of two-dimensional DNA crystals," Nature, Nature, vol. 394(6693), pages 539-544, August.
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