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

Author:

Tian XiangORCID,Liu Xiyu,Zhang Hongyan,Sun Minghe,Zhao Yuzhen

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.

Funder

National Natural Science Foundation of China

Social Science Fund Project of Shandong

Natural Science Foundation of Shandong Province

Youth Fund for Humanities and Social Sciences, Ministry of Education

China Postdoctoral Special Funding Project

China Postdoctoral Science Foundation

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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