The shortest path problem on large-scale real-road networks

Networks ◽  
2006 ◽  
Vol 48 (4) ◽  
pp. 182-194 ◽  
Author(s):  
G.A. Klunder ◽  
H.N. Post
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Road Networks ◽  
Shortest Path Problem

An exact method for the biobjective shortest path problem for large-scale road networks

2015 ◽  
Vol 242 (3) ◽  
pp. 788-797 ◽  
Author(s):  
Daniel Duque ◽  
Leonardo Lozano ◽  
Andrés L. Medaglia
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Road Networks ◽  
Shortest Path Problem ◽  
Exact Method

scholarly journals The MapReduce-based approach to improve the shortest path computation in large-scale road networks: the case of A* algorithm

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Wilfried Yves Hamilton Adoni ◽  
Tarik Nahhal ◽  
Brahim Aghezzaf ◽  
Abdeltif Elbyed
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Road Networks ◽  
A Algorithm ◽  
Path Computation ◽  
Shortest Path Computation

SH: A Novel Method for the Dynamic and Shortest Path Problem

2010 ◽  
Vol 129-131 ◽  
pp. 1013-1017
Author(s):  
Ya Fei Guo ◽  
Zheng Qin ◽  
Rong Hua Guo ◽  
Lei Ji
Keyword(s):  
Shortest Path ◽  
Heuristic Search ◽  
Large Scale ◽  
Ant Colony Algorithm ◽  
Real Life ◽  
Shortest Path Problem ◽  
Ant Colony ◽  
Current Path ◽  
Novel Method ◽  
Better Than

For the dynamic and shortest path problem, a novel algorithm SH(simulate human) is designed by simulating the process of our searching path in real life. The algorithm adopts the idea of heuristic search and integrates with the ant colony algorithm, in which the saved current path, the idea of “ask once every junction”, the bypassing barrier search and other some related definitions are proposed, as well as the ant colony algorithm is improved, so as to find the better solution and reduce the searching time. The experimental results show that the algorithm runs better than other existing methods. Moreover, it can find the shortest path or the approximate shortest one in a shorter time on road networks of any scales. Especially, SH algorithm is more effective for the large scale road network.

scholarly journals Finding Shortest Path for Road Network Using Dijkstra’s Algorithm

2019 ◽  
Vol 1 (2) ◽  
pp. 41-45
Author(s):  
Md. Almash Alam ◽  
Md. Omar Faruq
Keyword(s):  
Shortest Path ◽  
Road Network ◽  
Shortest Paths ◽  
Road Networks ◽  
Transportation Systems ◽  
Shortest Path Problem ◽  
Dijkstra’S Algorithm ◽  
Traffic Condition ◽  
Shortest Path Problems ◽  
Dijkstra's Algorithm

Roads play a Major role to the people live in various states, cities, town and villages, from each and every day they travel to work, to schools, to business meetings, and to transport their goods. Even in this modern era whole world used roads, remain one of the most useful mediums used most frequently for transportation and travel. The manipulation of shortest paths between various locations appears to be a major problem in the road networks. The large range of applications and product was introduced to solve or overcome the difficulties by developing different shortest path algorithms. Even now the problem still exists to find the shortest path for road networks. Shortest Path problems are inevitable in road network applications such as city emergency handling and drive guiding system. Basic concepts of network analysis in connection with traffic issues are explored. The traffic condition among a city changes from time to time and there are usually huge amounts of requests occur, it needs to find the solution quickly. The above problems can be rectified through shortest paths by using the Dijkstra’s Algorithm. The main objective is the low cost of the implementation. The shortest path problem is to find a path between two vertices (nodes) on a given graph, such that the sum of the weights on its constituent edges is minimized. This problem has been intensively investigated over years, due to its extensive applications in graph theory, artificial intelligence, computer network and the design of transportation systems. The classic Dijkstra’s algorithm was designed to solve the single source shortest path problem for a static graph. It works starting from the source node and calculating the shortest path on the whole network. Noting that an upper bound of the distance between two nodes can be evaluated in advance on the given transportation network.

A MapReduce-based approach for shortest path problem in large-scale networks

2015 ◽  
Vol 41 ◽  
pp. 151-165 ◽  
Author(s):  
Sabeur Aridhi ◽  
Philippe Lacomme ◽  
Libo Ren ◽  
Benjamin Vincent
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Shortest Path Problem ◽  
Large Scale Networks

scholarly journals DMGA: A Distributed Shortest Path Algorithm for Multistage Graph

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Huanqing Cui ◽  
Ruixue Liu ◽  
Shaohua Xu ◽  
Chuanai Zhou
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Structural Characteristics ◽  
Shortest Paths ◽  
Dynamic Programming Algorithm ◽  
Special Kind ◽  
Graph Algorithm ◽  
Shortest Path Problem ◽  
Programming Algorithm ◽  
Classical Dynamic

The multistage graph problem is a special kind of single-source single-sink shortest path problem. It is difficult even impossible to solve the large-scale multistage graphs using a single machine with sequential algorithms. There are many distributed graph computing systems that can solve this problem, but they are often designed for general large-scale graphs, which do not consider the special characteristics of multistage graphs. This paper proposes DMGA (Distributed Multistage Graph Algorithm) to solve the shortest path problem according to the structural characteristics of multistage graphs. The algorithm first allocates the graph to a set of computing nodes to store the vertices of the same stage to the same computing node. Next, DMGA calculates the shortest paths between any pair of starting and ending vertices within a partition by the classical dynamic programming algorithm. Finally, the global shortest path is calculated by subresults exchanging between computing nodes in an iterative method. Our experiments show that the proposed algorithm can effectively reduce the time to solve the shortest path of multistage graphs.

Robust Bi-objective Shortest Path Problem in Real Road Networks

2017 ◽  
pp. 128-136 ◽  
Author(s):  
Christian Cintrano ◽  
Francisco Chicano ◽  
Enrique Alba
Keyword(s):  
Shortest Path ◽  
Road Networks ◽  
Shortest Path Problem

scholarly journals FAST IMPLEMENTATION OF DIJKSTRA'S ALGORITHM FOR THE LARGE-SCALE SHORTEST PATH PROBLEM

2011 ◽  
Vol 54 (0) ◽  
pp. 58-83
Author(s):  
Yuichiro Yasui ◽  
Katsuki Fujisawa ◽  
Hiroshi Sasajima ◽  
Kazushige Goto
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Shortest Path Problem ◽  
Dijkstra’S Algorithm ◽  
Dijkstra's Algorithm ◽  
Fast Implementation
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