Results 21 to 30 of about 1,116,280 (113)

Shortest shortest path trees of a network

Discrete Applied Mathematics, 1996
If \(N\) is an undirected network where each edge has positive length, we may consider the distances of vertices from a specified internal point of an edge. A shortest path tree (SPT) rooted at \(s\) (possibly an internal point of an edge) is a spanning tree \(T\) of the network \(N[s]\) (i.e., \(N\) with \(s\) as possibly a new vertex) where for each ...
Pierre Hansen, Maolin Zheng
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Shortest Paths in Microseconds

CoRR, 2013
Extended version of WOSN'12 paper: new techniques (reduced memory, faster computations), distributed (MapReduce) algorithm, multiple paths between a source-destination ...
Rachit Agarwal 0001, Matthew Caesar 0001, Brighten Godfrey, Ben Y. Zhao   +3 more
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On Universal Shortest Paths [PDF]

, 2011
The universal combinatorial optimization problem (Univ-COP) generalizes classical and new objective functions for combinatorial problems given by a ground set, a set of feasible solutions and costs assigned to the elements in the ground set. The corresponding universal objective function is of the sum type and associates additional multiplicative ...
Lara Turner, Horst W. Hamacher
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Genetic algorithms with elitism-based immigrants for dynamic shortest path problem in mobile ad hoc networks [PDF]

, 2009
This article is posted here with permission from the IEEE - Copyright @ 2009 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic ...
Yang, S, Shengxiang Yang, Cheng, H, Hui Cheng, Cheng, Hui, Yang, Shengxiang   +5 more
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Multi-population genetic algorithms with immigrants scheme for dynamic shortest path routing problems in mobile ad hoc networks [PDF]

, 2010
Copyright @ Springer-Verlag Berlin Heidelberg 2010.The static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc ...
Yang, S, Shengxiang Yang, Cheng, H, Hui Cheng, Cheng, Hui, Yang, Shengxiang   +5 more
core   +1 more source

Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks [PDF]

, 2010
This article is posted here with permission of IEEE - Copyright @ 2010 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs)
Yang, S, Cheng, H, Cheng, Hui, Yang, Shengxiang, Wang, Fang, Wang, F   +5 more
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Finding next-to-shortest paths in a graph [PDF]

, 2004
We study the problem of finding the next-to-shortest paths in a graph. A next-to-shortest $(u,v)$-path is a shortest $(u,v)$-path amongst $(u,v)$-paths with length strictly greater than the length of the shortest $(u,v)$-path.
Krasikov, I, Krasikov, I., Noble, Steven, Noble, S D   +3 more
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Reconfiguring Shortest Paths in Graphs

Algorithmica, 2022
AbstractReconfiguring two shortest paths in a graph means modifying one shortest path to the other by changing one vertex at a time so that all the intermediate paths are also shortest paths. This problem has several natural applications, namely: (a) repaving road networks, (b) rerouting data packets in a synchronous multiprocessing setting, (c) the ...
Kshitij Gajjar, Agastya Vibhuti Jha, Manish Kumar 0011, Abhiruk Lahiri   +3 more
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Shortest-Path Kernels on Graphs [PDF]

Fifth IEEE International Conference on Data Mining (ICDM'05), 2006
Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels
Karsten M. Borgwardt, Hans-Peter Kriegel
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Time-dependent stochastic shortest path(s) algorithms for a scheduled transportation network [PDF]

, 2005
Following on from our work concerning travellers’ preferences in public transportation networks (Wu and Hartley, 2004), we introduce the concept of stochasticity to our algorithms.
Wu, Q, Al-Dabass, D, Hartley, JK
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