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

Date
2020-12-02
Authors
Tian, Xiang
Liu, Xiyu
Zhang, Hongyan
Sun, Minghe
Zhao, Yuzhen
Journal Title
Journal ISSN
Volume Title
Publisher
Public Library of Science (PLOS)
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.

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Citation
Tian, X., Liu, X., Zhang, H., Sun, M., & Zhao, Y. (2020). A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model. PLOS ONE, 15(12), e0242083. doi:10.1371/journal.pone.0242083
Department
Management Science and Statistics