Evolutionary DNA Computing Algorithm for Job Scheduling Problem

ABSTRACT

DNA computing techniques have interesting properties such as vast parallel computation attainment, organic edges, and tiny parts. These properties have attracted researchers from various fields (Bioinformatics, Biochemistry, and others). These techniques mainly rest on biochemical responses of molecules of DNA. Nonetheless, these biochemical responses might anneal in unsystematic fashion and conceivably generate inappropriate computations. This motivates prospects to utilize evolutionary computation as it lays importance on probabilistic and optimization search approaches. In this research study, the ability of DNA computing is demonstrated and verified by selecting the job scheduling problem (JSP). JSP can be easily tackled by a human or by using standard computers. A proposed evolutionary DNA algorithm is presented in this paper to solve the JSP; the proposed technique produces promising and better results than the standard DNA computing algorithm. Through adding supportive operations to the evolutionary operations, the performance becomes better; in addition, it has more solutions at the end, and therefore, the possibility of having an optimum or near optimum solution is increased, and the average number of solutions is improved.

KEYWORDS:

• DNA computation algorithm
• Evolutionary DNA algorithm
• Job scheduling problem
• Metaheuristics
• Parallel computation

ACKNOWLEDGEMENTS

Authors would like to thank both Salahaddin University-Erbil and University of Kurdistan-Hawler for their continuous support.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Additional information

Funding

University of Kurdistan Hewlêr [UKH-G5].

Notes on contributors

Gudar J. Ibrahim

Gudar J. Ibrahim obtained his MSc degree in software engineering from College of Engineering, Salahaddin University-Erbil, in 2012. He is an assistant lecturer at Salahaddin University-Erbil, Kurdistan.

E-mail: [email protected]

Tarik A. Rashid

Tarik A. Rashid received his PhD degree from University College Dublin, in 2006. He is a professor at the department of Computer Science and Engineering, University of Kurdistan Hewlêr, Kurdistan.

Ahmed T. Sadiq

Ahmed T. Sadiq is a professor of artificial intelligence in postgraduate studies at five Iraqi universities. He has supervised 14 PhD and 45 MSc theses.

E-mail: [email protected]