scholarly journals Search of the Shortest Path in a Communication Network with Fuzzy Cost Functions

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1534
Author(s):  
Lissette Valdés ◽  
Alfonso Ariza ◽  
Sira M. Allende ◽  
Alicia Triviño ◽  
Gonzalo Joya
Keyword(s):  
Communication Network ◽  
Shortest Path ◽  
Cost Allocation ◽  
Fuzzy Optimization ◽  
Triangular Fuzzy Number ◽  
Cost Functions ◽  
State Variables ◽  
Dijkstra Algorithm ◽  
Fuzzy Cost ◽  
Type V

A communication network management system takes the measurements of its state variables at specific instants of time, considering them constant in the interval between two consecutive measurements. Nevertheless, this assumption is not true, since these variables evolve in real time. Therefore, uncertainty is inherent in the processing of the measurements during the intervals so that they cannot be efficiently managed using crisp variables. In this paper, we face this problem by modeling the communications network as a type-V fuzzy graph, where both the nodes and the links are described with precision, but the cost of each link is modeled as a triangular fuzzy number. Different fuzzy cost allocation functions and fuzzy optimization strategies are described and applied to the search for the shortest path between two nodes. An experimental study has been conducted using two representative networks: the backbone network of Nippon Telegraph and Telephone Corporation (NTT) and the National Science Foundation’s Network (NFSNET). In these networks, our fuzzy cost functions and strategies have been compared with the well-known crisp equivalents. The optimal search strategies are based on the proposed Fuzzy Dijkstra Algorithm (FDA), which is described deeply. The simulation results demonstrate that in all cases the fuzzy alternatives surpass or equal the crisp equivalents with statistically significant values. Specifically, the so-called Strategy 8 presents the best throughput, as it significantly exceeds the performance of all those evaluated, achieving a Global Mean Delivery Rate (GMDR) close to 1.

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.

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