QRP02-4: Probabilistic Path Selection under Inaccuracy via Augmented Shortest Path Algorithms

2006 ◽  
Author(s):  
Suleyman Uludag ◽  
King-Shan Lui ◽  
Ziyneti Elif Uludag
Keyword(s):  
Shortest Path ◽  
Path Selection ◽  
Shortest Path Algorithms

Identifying Multiple and Reasonable Paths in Transportation Networks: A Heuristic Approach

1997 ◽  
Vol 1607 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Dongjoo Park ◽  
Laurence R. Rilett
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Heuristic Algorithms ◽  
Transportation Networks ◽  
Multiple Criteria Decision Making ◽  
Path Selection ◽  
Multiple Criteria ◽  
Transportation Engineering ◽  
Shortest Path Algorithm ◽  
Shortest Path Algorithms

A fundamental component of many transportation engineering applications is the identification of the route between a given origin and destination. Typically, some type of shortest-path algorithm is used for this task. However, shortest-path algorithms are only applicable when a single criterion, such as minimizing travel time, is used for path selection. When multiple criteria, such as the mean and variance of travel time, are used for path selection, then alternative-path identification methods must be found. The present objective is to develop an algorithm that can identify multiple and reasonable routes in transportation networks so that multiple-criteria decision-making techniques can be used in route selection. First, the definitions of single and multiple routes from a transportation engineering perspective are examined. It is indicated that although the traditional k-shortest-path algorithms can find routes with similar route travel times, the routes may be too similar with respect to the links used and consequently are not appropriate for certain transportation applications. A definition of a reasonable path is developed on the basis of transportation engineering rather than purely mathematical considerations. Two k-reasonable-path algorithms are then illustrated. These algorithms can be used to identify multiple and reasonable routes in transportation networks. Lastly, the two heuristic algorithms were tested on a network from Bryan to College Station, Texas, and the results were compared with the results obtained with a traditional k-shortest-path algorithm. It was found that the reasonable-path algorithms can identify routes that are similar in route travel time but significantly different in terms of the links used.

scholarly journals RCy3: Network biology using Cytoscape from within R

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 1774 ◽  
Author(s):  
Julia A. Gustavsen ◽  
Shraddha Pai ◽  
Ruth Isserlin ◽  
Barry Demchak ◽  
Alexander R. Pico
Keyword(s):  
Shortest Path ◽  
Future Development ◽  
Enrichment Analysis ◽  
Network Biology ◽  
R Package ◽  
Programming Environment ◽  
R Packages ◽  
R Programming ◽  
Shortest Path Algorithms ◽  
Rest Api

RCy3 is an R package in Bioconductor that communicates with Cytoscape via its REST API, providing access to the full feature set of Cytoscape from within the R programming environment. RCy3 has been redesigned to streamline its usage and future development as part of a broader Cytoscape Automation effort. Over 100 new functions have been added, including dozens of helper functions specifically for intuitive data overlay operations. Over 40 Cytoscape apps have implemented automation support so far, making hundreds of additional operations accessible via RCy3. Two-way conversion with networks from \textit{igraph} and \textit{graph} ensures interoperability with existing network biology workflows and dozens of other Bioconductor packages. These capabilities are demonstrated in a series of use cases involving public databases, enrichment analysis pipelines, shortest path algorithms and more. With RCy3, bioinformaticians will be able to quickly deliver reproducible network biology workflows as integrations of Cytoscape functions, complex custom analyses and other R packages.

Note on “Optimal path selection approach for fuzzy reliable shortest path problem”

2020 ◽  
Vol 39 (5) ◽  
pp. 7653-7656
Author(s):  
Ranjan Kumar ◽  
SA Edalatpanah ◽  
Hitesh Mohapatra
Keyword(s):  
Shortest Path ◽  
Fuzzy Systems ◽  
Optimal Path ◽  
Vital Role ◽  
Path Selection ◽  
Shortest Path Problem ◽  
Shortest Path Problems ◽  
Fuzzy Environment ◽  
Selection Approach ◽  
Arc Lengths

There are different conditions where SPP play a vital role. However, there are various conditions, where we have to face with uncertain parameters such as variation of cost, time and so on. So to remove this uncertainty, Yang et al. [1] “[Journal of Intelligent & Fuzzy Systems, 32(1), 197-205”] have proposed the fuzzy reliable shortest path problem under mixed fuzzy environment and claimed that it is better to use their proposed method as compared to the existing method i.e., “[Hassanzadeh et al.; A genetic algorithm for solving fuzzy shortest path problems with mixed fuzzy arc lengths, Mathematical and Computer Modeling, 57(2013) 84-99” [2]]. The aim of this note is, to highlight the shortcoming that is carried out in Yang et al. [1] article. They have used some mathematical incorrect assumptions under the mixed fuzzy domain, which is not true in a fuzzy environment.

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