scholarly journals Shortest Fuzzy Hamiltonian Cycle on Transportation Network Using Minimum Vertex Degree and Time-dependent Dijkstra’s Algorithm

2021 ◽  
Vol 54 (2) ◽  
pp. 348-353
Author(s):  
Esra Çakir ◽  
Ziya Ulukan ◽  
Tankut Acarman
Keyword(s):  
Hamiltonian Cycle ◽  
Transportation Network ◽  
Vertex Degree ◽  
Time Dependent ◽  
Dijkstra’S Algorithm ◽  
Dijkstra's Algorithm

Time-dependent Dijkstra’s algorithm under bipolar neutrosophic fuzzy environment

2021 ◽  
pp. 1-10
Author(s):  
Esra Çakır ◽  
Ziya Ulukan ◽  
Tankut Acarman
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Real Life ◽  
Time Dependent ◽  
Dijkstra’S Algorithm ◽  
Fuzzy Environment ◽  
Dijkstra's Algorithm ◽  
Fuzzy Graphs ◽  
Negative Statements ◽  
Shortest Path Algorithms

Determining the shortest path and calculating the shortest travel time of a complex networks are important for transportation problems. Numerous approaches has been developed to search shortest path on graphs, and one of the well-known is the Dijkstra’s label correcting algorithm. Dijkstra’s approach is capable of determining shortest path of directed or undirected graph with non-negative weighted arcs. To handle with uncertainty in real-life, the Dijkstra’s algorithm should be adapted to fuzzy environment. The weight of arc -which is the vague travel time between two nodes- can be expressed in bipolar neutrosophic fuzzy sets containing positive and negative statements. In addition, the weights of arcs in bipolar neutrosophic fuzzy graphs can be affected by time. This study proposes the extended Dijkstra’s algorithm to search the shortest path and calculate the shortest travel time on a single source time-dependent network of bipolar neutrosophic fuzzy weighted arcs. The proposed approach is illustrated, and the results demonstrate the validity of the extended algorithm. This article is intended to guide future shortest path algorithms on time-dependent fuzzy graphs.

scholarly journals Railway timetabling: a maximum bottleneck path algorithm for finding an additional train path

2020 ◽  
Author(s):  
Fredrik Ljunggren ◽  
Kristian Persson ◽  
Anders Peterson ◽  
Christiane Schmidt
Keyword(s):  
Experimental Evaluation ◽  
Temporal Distance ◽  
Dijkstra’S Algorithm ◽  
Passenger Traffic ◽  
Dijkstra's Algorithm ◽  
Railway Timetabling

Abstract We present an algorithm to insert a train path in an existing railway timetable close to operation, when we want to affect the existing (passenger) traffic as little as possible. Thus, we consider all other trains as fixed, and aim for a resulting train path that maximizes the bottleneck robustness, that is, a train path that maximizes the temporal distance to neighboring trains in the timetable. Our algorithm is based on a graph formulation of the problem and uses a variant of Dijkstra’s algorithm. We present an extensive experimental evaluation of our algorithm for the Swedish railway stretch from Malmö to Hallsberg. Moreover, we analyze the size of our constructed graph.

Smart Shopping Robot for Supermarkets using Dijkstra’s Algorithm with user Interface

2020 ◽  
pp. 193-203
Author(s):  
Stevens Johnson ◽  
V.M. Midhun ◽  
Nithin Issac ◽  
Ann Mariya Mathew ◽  
Shinosh Mathew
Keyword(s):  
User Interface ◽  
Dijkstra’S Algorithm ◽  
Dijkstra's Algorithm

scholarly journals Optimal power flow-path determination for voltage control in electricity distribution using the modified dijkstra’s algorithm

2021 ◽  
Vol 10 (2) ◽  
pp. 108
Author(s):  
Ofem Ajah Ofem ◽  
Moses Adah Agana ◽  
Ejogobe Owai E.
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Distribution Network ◽  
Flow Path ◽  
Path Model ◽  
Electricity Distribution ◽  
Dijkstra’S Algorithm ◽  
Shortest Path Problems ◽  
Dijkstra's Algorithm ◽  
Optimal Power

This paper examines the electric power distribution network system of the Port Harcourt Electricity Distribution Company (PHEDC); its shortcomings, costs and voltage loss in distribution with a view to finding optimal solution through determination of optimal power flow path. The Modified Dijsktra’s Algorithm was applied to generate optimal flow path model of the distribution network with seven (7) nodes from Afam Thermal Power Station (source) to the Calabar Distribution Centre (destination) via the interconnected substations. The structural design of the PHEDC distribution network and a review of relevant literatures on shortest path problems were adopted. The modified Dijkstra’s algorithm was simulated using JavaScript and is able to run on any web browser (Google Chrome, Mozilla Firefox, etc). It was applied to a practical 330kV network using the relevant data obtained from the company and the result shows the negative effect of distance on voltage quality. It was observed that the Modified Dijkstra’s Algorithm is suitable for determining optimal power flow path with up to 98 percent level of accuracy because of its suitability for determining the shortest route in both transportation and power energy distribution as well as its overall performance with minimal memory space and fast response time.  

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