Standard
Cumulative updating of network reliability with diameter constraint and network topology optimization. / Migov, Denis A.; Nechunaeva, Kseniya A.; Nesterov, Sergei N. et al.
Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings. ed. / Bernady O. Apduhan; Beniamino Murgante; Sanjay Misra; David Taniar; Carmelo M. Torre; Ana Maria A.C. Rocha; Shangguang Wang; Osvaldo Gervasi; Elena Stankova. Springer-Verlag GmbH and Co. KG, 2016. p. 141-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9786).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Migov, DA, Nechunaeva, KA, Nesterov, SN
& Rodionov, AS 2016,
Cumulative updating of network reliability with diameter constraint and network topology optimization. in BO Apduhan, B Murgante, S Misra, D Taniar, CM Torre, AMAC Rocha, S Wang, O Gervasi & E Stankova (eds),
Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9786, Springer-Verlag GmbH and Co. KG, pp. 141-152, 16th International Conference on Computational Science and Its Applications, ICCSA 2016, Beijing, China,
04.07.2016.
https://doi.org/10.1007/978-3-319-42085-1_11
APA
Migov, D. A., Nechunaeva, K. A., Nesterov, S. N.
, & Rodionov, A. S. (2016).
Cumulative updating of network reliability with diameter constraint and network topology optimization. In B. O. Apduhan, B. Murgante, S. Misra, D. Taniar, C. M. Torre, A. M. A. C. Rocha, S. Wang, O. Gervasi, & E. Stankova (Eds.),
Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings (pp. 141-152). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9786). Springer-Verlag GmbH and Co. KG.
https://doi.org/10.1007/978-3-319-42085-1_11
Vancouver
Migov DA, Nechunaeva KA, Nesterov SN
, Rodionov AS.
Cumulative updating of network reliability with diameter constraint and network topology optimization. In Apduhan BO, Murgante B, Misra S, Taniar D, Torre CM, Rocha AMAC, Wang S, Gervasi O, Stankova E, editors, Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings. Springer-Verlag GmbH and Co. KG. 2016. p. 141-152. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-42085-1_11
Author
Migov, Denis A. ; Nechunaeva, Kseniya A. ; Nesterov, Sergei N. et al. /
Cumulative updating of network reliability with diameter constraint and network topology optimization. Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings. editor / Bernady O. Apduhan ; Beniamino Murgante ; Sanjay Misra ; David Taniar ; Carmelo M. Torre ; Ana Maria A.C. Rocha ; Shangguang Wang ; Osvaldo Gervasi ; Elena Stankova. Springer-Verlag GmbH and Co. KG, 2016. pp. 141-152 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
BibTeX
@inproceedings{52edab743fce417ba10f92b13c498e25,
title = "Cumulative updating of network reliability with diameter constraint and network topology optimization",
abstract = "Reliability-based optimization of a network topology is to maximize the network reliability within certain constraints. For modeling of unrelaible networks we use random graphs due to their good applicability, wide facilities and profound elaborating. However, graph optimization problems in conditions of different constraints are NP-hard problems mostly. These problems can be effectively solved by optimization methods based on biological processes, such as genetic algorithms or clonal selection algorithms. As a rule, these techiques can provide an applicable solution for network topology optimization within an acceptable time. In order to speed up fitness function calculation, we improve operators of a genetic algorithm and a clonal selection algorithm by using the method of cumulative updating of lower and upper bounds of network reliability with diameter constraint. This method allows us to make a decision about the network reliability (or unreliability) with respect to a given threshold without performing the exhaustive calculation. Based on this method, we obtain the genetic algorithm and the clonal selection algorithm for network topology optimization. Some computational results are also presented for demonstration of an applicability of the proposed approach.",
keywords = "Clonal selection algorithm, Cumulative updating, Diameter constraint, Factoring method, Genetic algorithm, Network reliability, Network topology optimization, Random graph",
author = "Migov, {Denis A.} and Nechunaeva, {Kseniya A.} and Nesterov, {Sergei N.} and Rodionov, {Alexey S.}",
year = "2016",
doi = "10.1007/978-3-319-42085-1_11",
language = "English",
isbn = "9783319420844",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag GmbH and Co. KG",
pages = "141--152",
editor = "Apduhan, {Bernady O.} and Beniamino Murgante and Sanjay Misra and David Taniar and Torre, {Carmelo M.} and Rocha, {Ana Maria A.C.} and Shangguang Wang and Osvaldo Gervasi and Elena Stankova",
booktitle = "Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings",
address = "Germany",
note = "16th International Conference on Computational Science and Its Applications, ICCSA 2016 ; Conference date: 04-07-2016 Through 07-07-2016",
}
RIS
TY - GEN
T1 - Cumulative updating of network reliability with diameter constraint and network topology optimization
AU - Migov, Denis A.
AU - Nechunaeva, Kseniya A.
AU - Nesterov, Sergei N.
AU - Rodionov, Alexey S.
PY - 2016
Y1 - 2016
N2 - Reliability-based optimization of a network topology is to maximize the network reliability within certain constraints. For modeling of unrelaible networks we use random graphs due to their good applicability, wide facilities and profound elaborating. However, graph optimization problems in conditions of different constraints are NP-hard problems mostly. These problems can be effectively solved by optimization methods based on biological processes, such as genetic algorithms or clonal selection algorithms. As a rule, these techiques can provide an applicable solution for network topology optimization within an acceptable time. In order to speed up fitness function calculation, we improve operators of a genetic algorithm and a clonal selection algorithm by using the method of cumulative updating of lower and upper bounds of network reliability with diameter constraint. This method allows us to make a decision about the network reliability (or unreliability) with respect to a given threshold without performing the exhaustive calculation. Based on this method, we obtain the genetic algorithm and the clonal selection algorithm for network topology optimization. Some computational results are also presented for demonstration of an applicability of the proposed approach.
AB - Reliability-based optimization of a network topology is to maximize the network reliability within certain constraints. For modeling of unrelaible networks we use random graphs due to their good applicability, wide facilities and profound elaborating. However, graph optimization problems in conditions of different constraints are NP-hard problems mostly. These problems can be effectively solved by optimization methods based on biological processes, such as genetic algorithms or clonal selection algorithms. As a rule, these techiques can provide an applicable solution for network topology optimization within an acceptable time. In order to speed up fitness function calculation, we improve operators of a genetic algorithm and a clonal selection algorithm by using the method of cumulative updating of lower and upper bounds of network reliability with diameter constraint. This method allows us to make a decision about the network reliability (or unreliability) with respect to a given threshold without performing the exhaustive calculation. Based on this method, we obtain the genetic algorithm and the clonal selection algorithm for network topology optimization. Some computational results are also presented for demonstration of an applicability of the proposed approach.
KW - Clonal selection algorithm
KW - Cumulative updating
KW - Diameter constraint
KW - Factoring method
KW - Genetic algorithm
KW - Network reliability
KW - Network topology optimization
KW - Random graph
UR - http://www.scopus.com/inward/record.url?scp=84978869400&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-42085-1_11
DO - 10.1007/978-3-319-42085-1_11
M3 - Conference contribution
AN - SCOPUS:84978869400
SN - 9783319420844
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 141
EP - 152
BT - Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings
A2 - Apduhan, Bernady O.
A2 - Murgante, Beniamino
A2 - Misra, Sanjay
A2 - Taniar, David
A2 - Torre, Carmelo M.
A2 - Rocha, Ana Maria A.C.
A2 - Wang, Shangguang
A2 - Gervasi, Osvaldo
A2 - Stankova, Elena
PB - Springer-Verlag GmbH and Co. KG
T2 - 16th International Conference on Computational Science and Its Applications, ICCSA 2016
Y2 - 4 July 2016 through 7 July 2016
ER -
