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

2021 ◽  
Vol 297 ◽  
pp. 01062
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.

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.

Board Game Supporting Learning Prim’s Algorithm and Dijkstra’s Algorithm

2012 ◽  
pp. 256-270
Author(s):  
Wen-Chih Chang ◽  
Te-Hua Wang ◽  
Yan-Da Chiu
Keyword(s):  
Data Structure ◽  
Spanning Tree ◽  
Spanning Trees ◽  
Minimum Spanning Tree ◽  
Experimental Results ◽  
Dijkstra’S Algorithm ◽  
Board Game ◽  
Tree Algorithm ◽  
Dijkstra's Algorithm ◽  
Tree Algorithms

The concept of minimum spanning tree algorithms in data structure is difficult for students to learn and to imagine without practice. Usually, learners need to diagram the spanning trees with pen to realize how the minimum spanning tree algorithm works. In this paper, the authors introduce a competitive board game to motivate students to learn the concept of minimum spanning tree algorithms. They discuss the reasons why it is beneficial to combine graph theories and board game for the Dijkstra and Prim minimum spanning tree theories. In the experimental results, this paper demonstrates the board game and examines the learning feedback for the mentioned two graph theories. Advantages summarizing the benefits of combining the graph theories with board game are discussed.

scholarly journals Optimization of Shortest Path Problem using Dijkstra’s Algorithm in Imprecise Environment

2021 ◽  
Vol 10 (10) ◽  
pp. 216-221
Author(s):  
Samir Dey ◽  
Sriza Malakar ◽  
Shibnath Rajak
Keyword(s):  
Shortest Path ◽  
Shortest Path Problem ◽  
Dijkstra’S Algorithm ◽  
Dijkstra Algorithm ◽  
Numerical Example ◽  
Network Problem ◽  
Dijkstra's Algorithm

Dijkstra algorithm is a widely used algorithm to find the shortest path between two specified nodes in a network problem. In this paper, a generalized fuzzy Dijkstra algorithm is proposed to find the shortest path using a new parameterized defuzzification method. Here, we address most important issue like the decision maker’s choice. A numerical example is used to illustrate the efficiency of the proposed algorithm.

Board Game Supporting Learning Prim’s Algorithm and Dijkstra’s Algorithm

2010 ◽  
Vol 1 (4) ◽  
pp. 16-30
Author(s):  
Wen-Chih Chang ◽  
Te-Hua Wang ◽  
Yan-Da Chiu
Keyword(s):  
Data Structure ◽  
Spanning Tree ◽  
Spanning Trees ◽  
Minimum Spanning Tree ◽  
Experimental Results ◽  
Dijkstra’S Algorithm ◽  
Board Game ◽  
Tree Algorithm ◽  
Dijkstra's Algorithm ◽  
Tree Algorithms

The concept of minimum spanning tree algorithms in data structure is difficult for students to learn and to imagine without practice. Usually, learners need to diagram the spanning trees with pen to realize how the minimum spanning tree algorithm works. In this paper, the authors introduce a competitive board game to motivate students to learn the concept of minimum spanning tree algorithms. They discuss the reasons why it is beneficial to combine graph theories and board game for the Dijkstra and Prim minimum spanning tree theories. In the experimental results, this paper demonstrates the board game and examines the learning feedback for the mentioned two graph theories. Advantages summarizing the benefits of combining the graph theories with board game are discussed.

scholarly journals Dijkstra Algorithm for Determining the Shortest Path in the Case of Seven Hotels in Manado City Towards Manado’s Sam Ratulangi Airport.

d'CARTESIAN ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 158
Author(s):  
Yohana Permata Hutapea ◽  
Chriestie E.J.C. Montolalu ◽  
Hanny A.H. Komalig
Keyword(s):  
Graph Theory ◽  
Travel Time ◽  
Shortest Path ◽  
Travel Distance ◽  
Dijkstra’S Algorithm ◽  
Dijkstra Algorithm ◽  
Google Maps ◽  
Transportation Mode ◽  
Dijkstra's Algorithm ◽  
The Difference

Manado city has many notable tourist sites, resulting in the increase of the number of tourists visiting every year. Tourists require hotels with adequate facilities for their stay, such as 4-star hotels. After visiting Manado, tourists go back to where they come from. One of the transportation mode being used is airplanes. They then need a path to go through and not the usual one; they need the shortest path to get to Sam Ratulangi airport. Based on previous research, the shortest path is modeled by Graph Theory. Hotels will be represented as vertices, and the path from each hotels and to the airport will be represented as edges. The shortest path are searched by using Dijkstra’s Algorithm then will see the difference to shortest path from google maps. Based on the analysis results, Dijkstra’s Algorithm selects the shortest path with the smallest weight. The difference between Dijkstra’s Algorithm and google maps can be concluded that, in determining the shortest path used for the trip from the 4-star hotel to the airport, Dijkstra’s Algorithm is emphasized towards short travel distance, whereas google maps is emphasized more in short travel time.

scholarly journals A Constant-Factor Approximation for the Generalized Cable-Trench Problem

2019 ◽  
Author(s):  
Marcelo Benedito ◽  
Lehilton Pedrosa ◽  
Hugo Rosado
Keyword(s):  
Shortest Path ◽  
Steiner Tree ◽  
Spanning Tree ◽  
Optimization Problem ◽  
Minimum Spanning Tree ◽  
Weighted Graph ◽  
Constant Factor ◽  
Steiner Tree Problem ◽  
Negative Factor ◽  
Path Lengths

In the Cable-Trench Problem (CTP), the objective is to find a rooted spanning tree of a weighted graph that minimizes the length of the tree, scaled by a non-negative factor , plus the sum of all shortest-path lengths from the root, scaled by another non-negative factor. This is an intermediate optimization problem between the Single-Destination Shortest Path Problem and the Minimum Spanning Tree Problem. In this extended abstract, we consider the Generalized CTP (GCTP), in which some vertices need not be connected to the root, but may serve as cost-saving merging points; this variant also generalizes the Steiner Tree Problem. We present an 8.599-approximation algorithm for GCTP. Before this paper, no constant approximation for the standard CTP was known.

scholarly journals Journey to Crime Using Dijkstra’s Algorithm

2017 ◽  
Vol 1 (1) ◽  
pp. 1-14
Author(s):  
J. O. Olusina ◽  
J. B. Olaleye
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Shortest Path ◽  
Geographic Information ◽  
Service Area ◽  
Dijkstra’S Algorithm ◽  
Crime Mapping ◽  
Cost Matrix ◽  
Dijkstra's Algorithm ◽  
Journey To Crime

This paper describes some benefits of crime mapping in a Geographic Information Systems (G.I.S.) environment. The underlining principle of Journey to Crime was discussed. Crime Spots and Police Stations in the study area were mapped, Shortest-Path, Closest Facility, Service Area and OD (Origin – Destination) Cost Matrix were determined based on Dijkstra's Algorithm. Results show that the distribution of police stations does not correspond with the spread of crime spots.

scholarly journals Programmatic implementation of the Dijkstra algorithm in the Transact-SQL language using relational algebra

2020 ◽  
Vol 164 ◽  
pp. 10016
Author(s):  
Mikhail Urubkin ◽  
Vasiliy Galushka ◽  
Vladimir Fathi ◽  
Denis Fathi ◽  
Sofya Petrenkova
Keyword(s):  
Relational Algebra ◽  
Management Systems ◽  
Dijkstra’S Algorithm ◽  
Topical Issue ◽  
Dijkstra Algorithm ◽  
System Architectures ◽  
Dijkstra's Algorithm ◽  
Path Search ◽  
Sql Language ◽  
The Impact

The article is devoted to the topical issue of data processing in the database management systems. It presents a solution to the problem of finding paths in a graph using Dijkstra’s algorithm, set as a sequence of relational operations and functions of the Transact-SQL language. The efficiency of the known information system architectures and the impact of various ways of distributing functions between system components are reviewed. The article describes features of the relational algebra and the Transact-SQL operations, and provides a brief description of Dijkstra’s algorithm. For its programmatic implementation, several stages are defined, for each of which a formal description of the relational operations performed on it is given. The outputs of these operations are shown using the example of the database tables, and the algorithm to find the final path is given. The issues of the proposed method’s productivity and security of programmatic implementation of the path search in a graph are discussed separately.

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