Research on Route Optimization of Railway Passenger Transit Based on Shortest Path Dijkstra Algorithm

2022 ◽  
pp. 1167-1172
Author(s):  
Baochun Tian ◽  
Junhui Di
Keyword(s):  
Shortest Path ◽  
Route Optimization ◽  
Dijkstra Algorithm ◽  
Railway Passenger

Utilizing Restricted Direction Strategy and Binary Heap Technology to Optimize Dijkstra Algorithm in WebGIS

2009 ◽  
Vol 419-420 ◽  
pp. 557-560 ◽  
Author(s):  
Rui Li
Keyword(s):  
Shortest Path ◽  
Operating Efficiency ◽  
Dijkstra Algorithm ◽  
Shortest Path Algorithm ◽  
Research Focus ◽  
Network Information ◽  
The Core ◽  
Highway Network ◽  
Core Issue ◽  
Storage Structures

Shortest path is the core issue in application of WebGIS. Improving the efficiency of the algorithm is an urgent requirement to be resolved at present. By the lossy algorithm analyzing, which is the current research focus of the shortest path algorithm to optimize, utilizing adjacency table of storage structures, restricted direction strategy and binary heap technology to optimize the algorithm, thereby reduce the scale of algorithm to improve the operating efficiency of algorithm. This scheme has been applied in the simulation of the data downloaded from the Guangdong Provincial Highway Network Information System and satisfactory results have been obtained.

Finding the shortest path for a Hypergraph

2021 ◽  
pp. 2150120
Author(s):  
G. H. Shirdel ◽  
B. Vaez-Zadeh
Keyword(s):  
Graph Theory ◽  
Shortest Path ◽  
Complex Structure ◽  
Dijkstra Algorithm ◽  
Clique Graph ◽  
One To One

A hypergraph is given by [Formula: see text], where [Formula: see text] is a set of vertices and [Formula: see text] is a set of nonempty subsets of [Formula: see text], the member of [Formula: see text] is named hyperedge. So, a hypergraph is a nature generalization of a graph. A hypergraph has a complex structure, thus some researchers try to transform a hypergraph to a graph. In this paper, we define two graphs, Clique graph and Persian graph. These relations are one to one. We can find the shortest path between two vertices in a hypergraph [Formula: see text], by using the Dijkstra algorithm in graph theory on the graphs corresponding to [Formula: see text].

scholarly journals Research on Network Drop Truck Scheduling Based on Dijkstra Algorithm

2019 ◽  
Vol 25 ◽  
pp. 01001
Author(s):  
Yang Li ◽  
Luhua Zhao ◽  
Entong Wang
Keyword(s):  
Shortest Path ◽  
Freight Transportation ◽  
Vehicle Scheduling ◽  
Dijkstra Algorithm ◽  
Vehicle Dispatching ◽  
Truck Scheduling ◽  
Important Link ◽  
Transportation Route ◽  
Network Type

In view of the important link of vehicle dispatching under the network-type trailer-drop transport strategy of vehicle sharing, this paper uses JAVA to implement the Dijkstra algorithm for the transportation route based on the distance between stations and the demand of freight transportation, so as to find the shortest path, and then through the model of trailer-drop transport, an example is given. The advantages of this vehicle scheduling are analyzed.

An Efficient K-Shortest Paths Based Routing Algorithm

2012 ◽  
Vol 532-533 ◽  
pp. 1775-1779
Author(s):  
Jian Lian ◽  
Yan Zhang ◽  
Cheng Jiang Li
Keyword(s):  
Computer Networks ◽  
Shortest Path ◽  
Traffic Engineering ◽  
Routing Algorithm ◽  
Shortest Paths ◽  
Routing Algorithms ◽  
Dijkstra Algorithm ◽  
Link State

We present an efficient K-shortest paths routing algorithm for computer networks. This Algorithm is based on enhancements to currently used link-state routing algorithms such as OSPF and IS-IS, which are only focusing on finding the shortest path route by adopting Dijkstra algorithm. Its desire effect to achieve is through the use of K-shortest paths algorighm, which has been implemented successfully in some fileds like traffic engineering. The correctness of this Algorithm is discussed at the same time as long as the comparison with OSPF.

The Study of Diffraction Ray Tracing on the Surface of Airplane

2012 ◽  
Vol 433-440 ◽  
pp. 6345-6349
Author(s):  
Li Peng Deng ◽  
Xiao Ying Zhao ◽  
You Feng Chen ◽  
Wang Jing
Keyword(s):  
Ray Tracing ◽  
Shortest Path ◽  
Convex Surface ◽  
Local Algorithm ◽  
Dijkstra Algorithm ◽  
End Point

This article makes the surface of airplane into quadrilateral gridding by using the method of discrete gridding generation, and calculates the data of gridding by using the classical Dijkstra algorithm (local algorithm) which can seek the shortest path from the start point and the end point. With that we can achieve diffraction ray tracing. This method can be used for any convex surface of the diffraction ray tracing.

scholarly journals Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system

2021 ◽  
Vol 24 (2) ◽  
pp. 1173
Author(s):  
K. Ibrahim Ata ◽  
A. Che Soh ◽  
A. J. Ishak ◽  
H. Jaafar
Keyword(s):  
Shortest Path ◽  
Ant Colony Algorithm ◽  
Optimal Path ◽  
Search Tree ◽  
Binary Search ◽  
Ant Colony ◽  
Binary Search Tree ◽  
Dijkstra Algorithm ◽  
Dijkstra's Algorithm ◽  
Parking System

A common algorithm to solve the single-source shortest path (SSSP) is the Dijkstra algorithm. However, the traditional Dijkstra’s is not accurate and need more time to perform the path in order it should visit all the nodes in the graph. In this paper, the Dijkstra-ant colony algorithm (ACO) with binary search tree (BST) has been proposed. Dijkstra and ACO are integrated to produce the smart guidance algorithm for the indoor parking system. Dijkstra algorithm initials the paths to finding the shortest path while ACO optimizes the paths. BST has been used to store the paths that Dijkstra algorithm initialled. The proposed algorithm is aimed to control the shortest path as well as guide the driver towards the nearest vacant available space near the entrance. This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. Moreover, the reason behind using the BST is to make the generation of the path by Dijkstra’s algorithm more accurate and less time performance. The results show a range of 8.3% to 26.8% improvement in the proposed path compared to the traditional Dijkstra’s algorithm.

scholarly journals Teknologi Location Based Service (Global Positioning System) Pada Perangkat Mobile

2010 ◽  
Vol 1 (1) ◽  
pp. 61 ◽  
Author(s):  
Budi Yulianto
Keyword(s):  
Communication Technology ◽  
Global Positioning System ◽  
Shortest Path ◽  
Mobile Device ◽  
Positioning System ◽  
Dijkstra Algorithm ◽  
General Packet Radio Service ◽  
Location Based Service ◽  
Analysis And Design ◽  
Global Positioning

Article presents analysis and design of software using Location Based Service (LBS) that is part of communication technology based on geographic position. The goal of the research is designing LBS application to be implemented on mobile device that has GPS (Global Positioning System) technology and uses GPRS (General Packet Radio Service) to connect to server for generating shortest path by Dijkstra algorithm method Fibonacci Heap. Software development method used is LBS application implemented on mobile device. Conclusion of the research has shown that shortest path generated using Dijkstra algorithm method Fibonacci Heap as single source shortest path is faster than Dijkstra algorithm and Bellman Ford.

scholarly journals The Implementation of Kruskal’s Algorithm for Minimum Spanning Tree in a Graph

2021 ◽  
Vol 348 ◽  
pp. 01001
Author(s):  
Paryati ◽  
Krit Salahddine
Keyword(s):  
Shortest Path ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Dijkstra’S Algorithm ◽  
Dijkstra Algorithm ◽  
Application System ◽  
Path Creation ◽  
Dijkstra's Algorithm

Kruskal’s Algorithm is an algorithm used to find the minimum spanning tree in graphical connectivity that provides the option to continue processing the least-weighted margins. In the Kruskal algorithm, ordering the weight of the ribs makes it easy to find the shortest path. This algorithm is independent in nature which will facilitate and improve path creation. Based on the results of the application system trials that have been carried out in testing and comparisons between the Kruskal algorithm and the Dijkstra algorithm, the following conclusions can be drawn: that a strength that is the existence of weight sorting will facilitate the search for the shortest path. And considering the characteristics of Kruskal’s independent algorithm, it will facilitate and improve the formation of the path. The weakness of the Kruskal algorithm is that if the number of nodes is very large, it will be slower than Dijkstra’s algorithm because it has to sort thousands of vertices first, then form a path.

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