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An algorithm for ranking quickest simple paths

TLDR
It is shown that the worst-case computational time complexity of the algorithm presented is O(Kr(m+n logn)), which is also the best-known complexity to solve this problem.
About
This article is published in Computers & Operations Research.The article was published on 2005-03-01 and is currently open access. It has received 62 citations till now. The article focuses on the topics: Time complexity & Average-case complexity.

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Routing, Flow, And Capacity Design In Communication And Computer Networks

TL;DR: Throughout, the authors focus on the traffic demands encountered in the real world of network design, and their generic approach allows problem formulations and solutions to be applied across the board to virtually any type of backbone communication or computer network.
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Internet packet routing: Application of a K-quickest path algorithm

TL;DR: This paper describes a study on the application of an algorithm to rank the K-quickest paths to the routing of data packets in Internet networks by considering two types of random generated networks and results concerning the average CPU times of the algorithm are presented.
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Maintenance reliability estimation for a cloud computing network with nodes failure

TL;DR: An algorithm to estimate the performance of a CCN under maintenance budget with nodes failure is proposed to measure the capability that the CCN can send d units of data from the cloud to the client through multiple paths under the maintenance budget and time constraints.
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A comprehensive survey on the quickest path problem

TL;DR: The classification presented led to the proposal of a new variant of a known K quickest loopless paths algorithm, and some comparative empirical results on applications of quickest path algorithms are mentioned.
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Computation of the Reliable and Quickest Data Path for Healthcare Services by Using Service-Level Agreements and Energy Constraints

TL;DR: Analysis indicates that the SERQPP path is a reliable and quickest option for data transmission in remote healthcare applications and quantitative and qualitative comparative study shows that the proposed algorithm outperforms in computation ofSERQPP without increasing the time complexity.
References
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Journal ArticleDOI

A note on two problems in connexion with graphs

TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
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Finding the K Shortest Loopless Paths in a Network

Jin Y. Yen
- 01 Jul 1971 - 
TL;DR: The significance of the new algorithm is that its computational upper bound increases only linearly with the value of K, so it is extremely efficient as compared with the algorithms proposed by Bock, Kantner, and Haynes and others.
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An efficient algorithm for K shortest simple paths

TL;DR: This article gives an efficient algorithm for obtaining K shortest simple paths between two specified nodes in an undirected graph G with non-negative edge lengths, which is better than those realized by existing algorithms.
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The quickest path problem

TL;DR: If the general algorithm is used as a preprocessing step to handle the input network N, then the problem of finding a quickest path for a given value of σ can be solved in time O(log m).
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Algorithms for the quickest path problem and the enumeration of quickest paths

TL;DR: An alternative algorithm for the single pair quickest path problem with same time complexity and less space requirement is developed and an algorithm to enumerate the first m quickest paths to send a given amount of data with time complexity O(rmne + rmn2 log n) time is developed.
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Frequently Asked Questions (6)
Q1. What contributions have the authors mentioned in the paper "An algorithm for ranking quickest simple paths" ?

In this paper, an algorithm for ranking loopless paths in undirected networks, according to the transmission time, is presented. Finally, comparative computational results, with other algorithms for the same problem, are reported. 

In the tests presented K = 100 paths were ranked in undirected networks with both lead times and capacities uniformly generated in {1; : : : ; 100}, s and t are randomly chosen in {1; : : : ; n}, and =1000. 

If there exists a path from s to t deviating from p∗ before v ∈p∗, then the shortest one is either of type 1 or 2:Type 1: Ts(u) Tt(u), with s(u)¡ , Type 2: Ts(u) (u; v) Tt(v), with (u; v) ∈Ts ∪Tt and s(u)¡ 

In fact, in the Hrst one, computing new paths is alternated with determining each pk , while in the second all paths are generated before p1; : : : ; pK can be known. 

In this paper, a new algorithm for ranking quickest paths on undirected networks, which is an adaptation of Katoh et al.’s algorithm (of the same type of the adaptation of Yen’s algorithm made by Rosen et al.), was presented. 

Katoh et al. noticed thatP j k(v ; v )− {pk}=Pjk+1(v ; vd(pk)) ∪Pjk+1(vd(pk); v ) ∪Pkk+1(vd(pk)+1; t):The process to determine the shortest path in each of those subsets, say Pjk(vx; vy), uses a Yen-like procedure.