Standard

Hamiltonian path problem : The performance comparison deoxyribonucleic acid computing and the branch-and-bound method. / Sergeenko, A. N.; Granichin, O. N.; Yakunina, M. V.

In: Journal of Physics: Conference Series, Vol. 1536, No. 1, 012003, 21.05.2020.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Sergeenko, AN, Granichin, ON & Yakunina, MV 2020, 'Hamiltonian path problem: The performance comparison deoxyribonucleic acid computing and the branch-and-bound method', Journal of Physics: Conference Series, vol. 1536, no. 1, 012003. https://doi.org/10.1088/1742-6596/1536/1/012003

APA

Sergeenko, A. N., Granichin, O. N., & Yakunina, M. V. (2020). Hamiltonian path problem: The performance comparison deoxyribonucleic acid computing and the branch-and-bound method. Journal of Physics: Conference Series, 1536(1), [012003]. https://doi.org/10.1088/1742-6596/1536/1/012003

Vancouver

Sergeenko AN, Granichin ON, Yakunina MV. Hamiltonian path problem: The performance comparison deoxyribonucleic acid computing and the branch-and-bound method. Journal of Physics: Conference Series. 2020 May 21;1536(1). 012003. https://doi.org/10.1088/1742-6596/1536/1/012003

Author

Sergeenko, A. N. ; Granichin, O. N. ; Yakunina, M. V. / Hamiltonian path problem : The performance comparison deoxyribonucleic acid computing and the branch-and-bound method. In: Journal of Physics: Conference Series. 2020 ; Vol. 1536, No. 1.

BibTeX

@article{13b87f7631634301bc6595b51368f345,
title = "Hamiltonian path problem: The performance comparison deoxyribonucleic acid computing and the branch-and-bound method",
abstract = "In this article different approaches to one of the most popular combinatorial problem - the Hamiltonian path problem - are illustrated and compared between each other. It is shown that it becomes inefficient to use branch-and-bound method, the most popular method which is realized on a computer, from the counted number of vertices because of its exponentially growing complexity, one more algorithm which is based on working with deoxyribonucleic acid (DNA) molecules in a laboratory is analysed. That method works parallel and has linearly growing time consumption. Due to the improvements in the biophysics methods, which are needed for DNA computing, that algorithm became much faster than it was several years ago and it is now possible to add some new stages in DNA computing, which are shown in this paper.",
author = "Sergeenko, {A. N.} and Granichin, {O. N.} and Yakunina, {M. V.}",
year = "2020",
month = may,
day = "21",
doi = "10.1088/1742-6596/1536/1/012003",
language = "English",
volume = "1536",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "1",
note = "International Workshop Navigation and Motion Control 2019, NMC 2019 ; Conference date: 16-09-2019 Through 20-09-2019",

}

RIS

TY - JOUR

T1 - Hamiltonian path problem

T2 - International Workshop Navigation and Motion Control 2019, NMC 2019

AU - Sergeenko, A. N.

AU - Granichin, O. N.

AU - Yakunina, M. V.

PY - 2020/5/21

Y1 - 2020/5/21

N2 - In this article different approaches to one of the most popular combinatorial problem - the Hamiltonian path problem - are illustrated and compared between each other. It is shown that it becomes inefficient to use branch-and-bound method, the most popular method which is realized on a computer, from the counted number of vertices because of its exponentially growing complexity, one more algorithm which is based on working with deoxyribonucleic acid (DNA) molecules in a laboratory is analysed. That method works parallel and has linearly growing time consumption. Due to the improvements in the biophysics methods, which are needed for DNA computing, that algorithm became much faster than it was several years ago and it is now possible to add some new stages in DNA computing, which are shown in this paper.

AB - In this article different approaches to one of the most popular combinatorial problem - the Hamiltonian path problem - are illustrated and compared between each other. It is shown that it becomes inefficient to use branch-and-bound method, the most popular method which is realized on a computer, from the counted number of vertices because of its exponentially growing complexity, one more algorithm which is based on working with deoxyribonucleic acid (DNA) molecules in a laboratory is analysed. That method works parallel and has linearly growing time consumption. Due to the improvements in the biophysics methods, which are needed for DNA computing, that algorithm became much faster than it was several years ago and it is now possible to add some new stages in DNA computing, which are shown in this paper.

UR - http://www.scopus.com/inward/record.url?scp=85085470707&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1536/1/012003

DO - 10.1088/1742-6596/1536/1/012003

M3 - Conference article

AN - SCOPUS:85085470707

VL - 1536

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012003

Y2 - 16 September 2019 through 20 September 2019

ER -

ID: 60761458