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Thi-Tuyet-Loan Pham

dblp:03/7018 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Network optimization and economics · 67% Routing and switching · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network optimization and economics
network design
0.112005
Design of capacitated survivable networks with a single facility · IEEE/ACM Trans. Netw. 2005
Routing and switching › routing › routing control
rerouting
0.112005
Design of capacitated survivable networks with a single facility · IEEE/ACM Trans. Netw. 2005
Network optimization and economics › network design
survivable network design
0.112005
Design of capacitated survivable networks with a single facility · IEEE/ACM Trans. Netw. 2005

Methods — techniques the papers use, named apart from their topics

mixed integer linear programming · 0.1cutting planes · 0.1benders decomposition · 0.1
YearPublicationVenuePosition
2005 Design of capacitated survivable networks with a single facility
abstract
In this paper we focus on the single-facility capacitated survivable network design problem. We optimize simultaneously the network topology and the link dimensioning in order to route all traffic commodities according to survivability requirements. The latter are actually expressed in terms of the spare capacity required to address link failures in the context of different rerouting strategies. We present a mixed-integer linear programming model solved by combining several approaches. To tackle the high dimensionality and to separate the continuous and integer variables, we use Benders' decomposition and a cutting-plane approach. Going beyond the proposed method itself, we examine and compare two well-known restoration techniques: local and end-to-end reroutings. Numerous computational results for realistic network instances provide a comparison of these rerouting mechanisms in terms of installed capacities, network density as well as overall costs and CPU time.
Hervé Kerivin, Dritan Nace, Thi-Tuyet-Loan Pham
IEEE/ACM Trans. Netw.3