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Journal articles on the topic 'Algorithm of Dijkstra'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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1

Dermawan, Tri Setya. "Comparison of Dijkstra dan Floyd-Warshall Algorithm to Determine the Best Route of Train." IJID (International Journal on Informatics for Development) 7, no. 2 (January 7, 2019): 8. http://dx.doi.org/10.14421/ijid.2018.07202.

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Abstract - The best route is the path found based on the minimum price of a train journey using the Dijkstra and Floyd-Warshall algorithms. This study aims to find out the comparison of Dijkstra and Floyd-Warshall algorithms in finding the best path on a train trip. The results of route discovery will be displayed in a web-based application using the PHP programming language and MySQL database. The results of these two algorithms are compared using 4 parameters: time complexity, memory complexity, level of completion and level of optimization.Based on the comparison results from the implementation that Dijkstra's algorithm has a time complexity of 81 faster than the Floyd-Warshall algorithm. For the memory complexity, Dijkstra's algorithm uses a memory of 512616 bytes less than the Floyd-Warshall algorithm for the executive category. Whereas for the economic category the Dijkstra algorithm uses a memory of 482488 bytes less than the Floyd-Warshall algorithm. For the level of completion of the two algorithms, there is no error. In addition, for the level of optimization the Dijkstra algorithm has advantages in this study, namely the data used is dynamic or variable data in each stage of the process.

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2

Wayahdi, Muhammad Rhifky, Subhan Hafiz Nanda Ginting, and Dinur Syahputra. "Greedy, A-Star, and Dijkstra’s Algorithms in Finding Shortest Path." International Journal of Advances in Data and Information Systems 2, no. 1 (February 1, 2021): 45–52. http://dx.doi.org/10.25008/ijadis.v2i1.1206.

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The problem of finding the shortest path from a path or graph has been quite widely discussed. There are also many algorithms that are the solution to this problem. The purpose of this study is to analyze the Greedy, A-Star, and Dijkstra algorithms in the process of finding the shortest path. The author wants to compare the effectiveness of the three algorithms in the process of finding the shortest path in a path or graph. From the results of the research conducted, the author can conclude that the Greedy, A-Star, and Dijkstra algorithms can be a solution in determining the shortest path in a path or graph with different results. The Greedy algorithm is fast in finding solutions but tends not to find the optimal solution. While the A-Star algorithm tends to be better than the Greedy algorithm, but the path or graph must have complex data. Meanwhile, Dijkstra's algorithm in this case is better than the other two algorithms because it always gets optimal results.

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3

Sedeño-noda, Antonio, and Marcos Colebrook. "A biobjective Dijkstra algorithm." European Journal of Operational Research 276, no. 1 (July 2019): 106–18. http://dx.doi.org/10.1016/j.ejor.2019.01.007.

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4

Dinitz, Yefim, and Rotem Itzhak. "Hybrid Bellman–Ford–Dijkstra algorithm." Journal of Discrete Algorithms 42 (January 2017): 35–44. http://dx.doi.org/10.1016/j.jda.2017.01.001.

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5

Ding, Ming Li. "Optimal Path Algorithm Analysis of GPS Navigation Based on A* Algorithm." Applied Mechanics and Materials 484-485 (January 2014): 982–85. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.982.

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The optimal path algorithm analysis of GPS navigation in taxi management system based on A* algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as time-consuming and low efficiency in Dijkstra algorithm with traversal search for each node, A* algorithm could help the taxi find the optimal path and bring convenience for traffic management.

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6

Maekawa, Kotaro, Kazuhito Sawase, and Hajime Nobuhara. "Multi-Resolution Dijkstra Method Based on Multi-Agent Simulation and its Application to Genetic Algorithm for Classroom Optimization." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 2 (March 20, 2014): 113–20. http://dx.doi.org/10.20965/jaciii.2014.p0113.

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The combinatorial optimization problem of university classroom schedule assignments is formulated using multiagent simulation and genetic algorithms in the evaluation and optimization process. The method we propose consists of global and local multiagent planning. Conventional global planning requires setting subgoals manually, which became a bottleneck in optimization. To solve this problem, a multi-resolution Dijkstra method for selected autonomously, assuming eight classrooms as a real University of Tsukuba building and 250 agents, we confirmed the effectiveness of the proposed multi-resolution Dijkstra’s algorithm as for both global and local route selections, compared to the uniform Dijkstra’s method.

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Hartanto, Anggit Dwi, Aji Surya Mandala, Dimas Rio P.L., Sidiq Aminudin, and Andika Yudirianto. "Implementasi Algoritma Dijkstra Pada Game Pacman." CCIT Journal 12, no. 2 (August 19, 2019): 170–76. http://dx.doi.org/10.33050/ccit.v12i2.687.

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Pacman is one of the labyrinth-shaped games where this game has used artificial intelligence, artificial intelligence is composed of several algorithms that are inserted in the program and Implementation of the dijkstra algorithm as a method of solving problems that is a minimum route problem on ghost pacman, where ghost plays a role chase player. The dijkstra algorithm uses a principle similar to the greedy algorithm where it starts from the first point and the next point is connected to get to the destination, how to compare numbers starting from the starting point and then see the next node if connected then matches one path with the path). From the results of the testing phase, it was found that the dijkstra algorithm is quite good at solving the minimum route solution to pursue the player, namely by getting a value of 13 according to manual calculations

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8

Kartika, Winanda. "MODEL TRANSPORTASI PENGIRIMAN PRODUK PERISHABLE DENGAN MULTI KENDARAAN." Jurnal Manajemen Industri dan Logistik 3, no. 1 (May 10, 2019): 57–74. http://dx.doi.org/10.30988/jmil.v3i1.72.

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Abstract : According to Graf theory, the shortest path determination is a problem of looking for a path between two vertices in a weighted graph to obtain the minimum amount of weight.The determination of the shortest path problem also called optimization problem. Several algorithms have been developed in solving this problem. Each algorithm has a different way of solving a particular problem. In this study, the development of algorithms was carried out to determine the critical path from one origin point to one destination point on a network for the delivery of perishable products that limited time window to minimize the total cost and the selection of vehicles that will be used for solving the problem.The Algorithm that developed is Dijkstra algorithm. The first stages of the algorithm development is to modify the network of the studied problem by making the network replication. The second stage is to make problem-solving steps to minimize the total cost, consists of a fixed cost, variable cost, vehicle turnover costs, deterioration cost and parking fees with modified Dijkstra algorithm because the problems can not be modeled mathematically.To test the developed algorithm, we used numerical examples with hypothetical dataKeywords: perishable product; deterioration; time window; modified Dijkstra algorithmAbstrak : Menurut teori Graf, penentuan rute terpendek merupakan suatu persoalan mencari lintasan antara dua buah simpul pada graf berbobot untuk mendapatkan jumlah bobot yang paling minimum. Permasalahan penentuan rute terpendek disebut juga masalah optimasi.Beberapa algoritma telah dikembangkan dalam pemecahan masalah ini. Setiap algoritma memiliki cara yang berbeda dalam menyelesaikan suatu permasalahan tertentu. Pada penelitian ini, dilakukan pengembangan algoritma untuk menentukan lintasan kritis dari satu titik asal ke satu titik tujuan pada suatu jaringan untuk pengiriman produk perishable dan dibatasi jendela waktu dengan meminimumkan total biaya sekaligus pemilihan jenis kendaraan yang akan digunakan untuk pemecahan masalah. Algoritma yang dikembangkan adalah Algoritma Dijkstra. Tahapan awal pengembangan algoritma adalah memodifikasi jaringan dari masalah yang diteliti dengan cara membuat replikasi jaringan. Tahapan kedua adalah membuat langkah pemecahan masalah untuk meminimumkan total biaya yaitu biaya tetap, biaya variabel, biaya pergantian kendaraan, biaya deteriorasi dan biaya tunggu dengan modifikasi Algoritma Dijkstra. Modifikasi Dijkstra dilakukan karena permasalahan yang diteliti tidak bisa dimodelkan secara matematis. Pengujian algoritma menggunakan contoh numerik dengan data hipotetik.Kata kunci: produk perishable; deteriorasi; jendela waktu; modifikasi Algoritma Dijkstra.

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9

Sun, Ya Qi, Yu Liu, and Kuo Hua Xiao. "Shortest Travel Path Searching System Based on Dijkstra Algorithm." Applied Mechanics and Materials 198-199 (September 2012): 1395–98. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.1395.

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The existing transportation service system in public travel route can not satisfy the people's actual travel need because of various technologies reasons. In our study, we set the tourist attractions as a vertex, and simplified the traditional algorithm for complex network computing. Aim to use the advantage of Dijkstra algorithm, the Dijkstra algorithm was applied to tourism path search. The experimental results have illustrated that the Dijkstra algorithm can accomplish a good result in search efficiency.

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10

Sun, Hong Xia, and Zheng Zhang. "Application of Shortest-Path Algorithm in Embedded GIS System." Advanced Materials Research 663 (February 2013): 626–31. http://dx.doi.org/10.4028/www.scientific.net/amr.663.626.

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The shortest-path is an important issue in GIS network analysis, and its implementation in embedded systems has already been used widely in the mobile-device-based GPS navigation and city emergency response system fields. Based on our analysis and verification of the Dijkstra algorithm’s application to road network analysis, we presented in detail the design and program implementation of the Dijkstra algorithm and its flow chart. In this paper, the shortest-path example based on Dijkstra algorithm，which was developed in the MapXmobile5.0 and EVC4.0 environment, has been applied to embedded GIS system successfully. The comparison between the results from the program and manually obtained results has shown the Dijkstra algorithm’s feasibility and accuracy.

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11

Salman et al., Mustafa I. "Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms." Baghdad Science Journal 17, no. 1(Suppl.) (March 18, 2020): 0391. http://dx.doi.org/10.21123/bsj.2020.17.1(suppl.).0391.

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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we evaluate the video transmission over the SDN with ‎Bellman Ford algorithm. Then, because the limitation of Bellman ford ‎algorithm, the Dijkstra algorithm is used to change the path when a congestion occurs. Furthermore, the Dijkstra algorithm is used with two ‎controllers to reduce the time consumed by the SDN controller. ‎ POX and Pyretic SDN controllers are used such that POX controller is ‎responsible for the network monitoring, while Pyretic controller is responsible for the ‎routing algorithm and path selection. Finally, a modified Dijkstra algorithm is further proposed and evaluated with two ‎controllers to enhance the performance. The results show that the modified Dijkstra algorithm outperformed the other approaches in the aspect of QoS parameters.

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12

Mo, Tai Ping, Hui Huang Zhao, and Wei Mo. "Design and Implementation of Shortest Travel Path Searching Based on Improved Dijkstra Algorithm." Applied Mechanics and Materials 157-158 (February 2012): 390–94. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.390.

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The existing transportation service system in public travel route can not satisfy the people's actual travel need because of various technologies reasons. In our study, we set the tourist attractions as a vertex, and simplified the traditional algorithm for complex network computing. Aim to improve the disadvantage of tradition Dijkstra algorithm, an improve algorithm was proposed to improve the path search efficiency. Then the improved Dijkstra algorithm was applied to tourism path search. The experimental results have illustrated that the improved Dijkstra algorithm can accomplish a better result and improve path search efficiency.

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13

Guo, Nan Chu. "A Solution to Best Itinerary Problem Based on Strategy Set under Dijkstra Algorithm." Applied Mechanics and Materials 333-335 (July 2013): 1442–45. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1442.

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The best itinerary problem has been a heat topic for several decades. Among those sophisticated methods used for choosing paths, Dijkstra algorithm is a simple but powerful method. However, Dijkstra algorithm is restricted because of 3 reasons. Firstly, the weight of each path must be a constant value. Secondly, the algorithm only represents the best path, disregards the second and third best paths. Thirdly, the weights only represent a single variable, which cannot be used to represent two different variables simultaneously. In this paper, we use a Filtering Algorithm based on Lagrange relaxation method and ordinal selection to overcome these weaknesses. In our OLR Dijkstra algorithm, strategy set of choosing paths shows a strong stability and reliability facing different probabilities situations. Only 13.2% diversity degree was found when path efficiency varied from 100% to 11.1%. Smallest time complexity of the OLR Dijkstra algorithm is 2 times than normal Dijsktra, which is .

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14

Lian, Jian, Yan Zhang, and Cheng Jiang Li. "An Efficient K-Shortest Paths Based Routing Algorithm." Advanced Materials Research 532-533 (June 2012): 1775–79. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.1775.

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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.

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15

Wang, Yu, Wei Huang, Yue Li, Qing Bo Tu, and Xin Tain. "Optimal Design of Transmission Line Route Based on GIS." Applied Mechanics and Materials 644-650 (September 2014): 3522–27. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3522.

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Transmission line route reflects the geospatial constraints on the grid. Environmental factors affecting the power transmission line route design are diverse and complex. This paper studies the method based on GIS (Geographic Information System) and Dijkstra algorithm. Establish environmental factors hierarchical model of transmission line route design using IAHP and gridded map and obtain each grid’s weight. Take into account weight of each grid’s environmental factors and number of the corner in order to build the branch weights of Dijkstra algorithm. After that the optimal route can be obtained using Dijkstra algorithm.

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16

Wahyuningsih, Delpiah, and Erzal Syahreza. "Shortest Path Search Futsal Field Location With Dijkstra Algorithm." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 12, no. 2 (July 31, 2018): 161. http://dx.doi.org/10.22146/ijccs.34513.

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Pangkalpinang City is a city where futsal field rentals are experiencing growth and improvement. The number of lovers of futsal sport from outside Pangkalpinang city, especially those who are less aware of the streets in Pangkalpinang city will have little difficulty in accessing futsal field places in this city because they do not know in detail information about the route to the futsal field. This research can facilitate futsal players in searching shortest path futsal field with algorithm dijkstra. The dijkstra algorithm determines the shortest path by computing the nodes passed from the initial node to the destination node. Dijkstra algorithm by forming the node graph, the new node then perform the calculation of the number of nodes that will form a new node for the determination of the node to be passed so that the algorithm dijkstra find the smallest node that will form the shortest path in the geographic information system. This system displays the shortest route from the user position to the futsal field which is the destination in the city of Pangkalpinang and surrounding areas.

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17

Jia, Qi, Yulei Liao, Peihong Xu, Zixiao Wang, Shuo Pang, and Xiangjie Li. "Long-Endurance Dynamic Path Planning Method of NSV Considering Wind Energy Capture." Journal of Marine Science and Engineering 9, no. 8 (August 14, 2021): 878. http://dx.doi.org/10.3390/jmse9080878.

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To meet the mission requirements of long-endurance and unmanned marine environment observation, the natural energy-driven unmanned surface vehicle (NSV) usually takes special sailing paths to increase energy capture to achieve the purpose of improving endurance. Aiming at the route planning problems of the “Wave Rider” NSV in the time-varying ocean wind field, this paper is organized as follows. Firstly, a visual modeling method of the real-time-varying ocean wind field for NSV is proposed. Then, through the wind energy capture experiment, the NSV system energy net output model is calculated, and a Dynamic Dijkstra algorithm considering wind energy capture (DW–Dijkstra) has been proposed in this paper based on a Dijkstra algorithm, of which weight function has been improved. Accordingly, the NSV long-endurance dynamic path planning method is designed. Finally, the DW–Dijkstra algorithm has been verified through a set of comparison simulations and a set of semi-physical comparison simulations. The results show that the DW–Dijkstra algorithm can plan a collision-free and high-efficiency energy capture path in the real-time-varying ocean wind field environment in the southern waters of China. Compared with the traditional A* algorithm and the Wind_A* algorithm, the proposed method can save energy by between 15.07% and 6.50%, respectively, which effectively increases the endurance of the NSV.

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Gong, Peng, Hong Wen Zang, and Ren Qian Lan. "Realization of the Optimization of Dijkstra Algorithm in Vehicle Navigation." Advanced Materials Research 709 (June 2013): 399–403. http://dx.doi.org/10.4028/www.scientific.net/amr.709.399.

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Vehicle navigation plays an important part in intelligent transportation. The optimal route of navigation was selected based on the optimization of the algorithm of Dijkstra in topology storage structure, node storage order in topology network and route weight of Dijkstra, thus reducing participating nodes, advancing optimization speed and improving efficiency in optimization process.

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Zhang, Feng, Ranfei Xia, and Xinxing Chen. "An optimal trajectory planning algorithm for autonomous trucks: Architecture, algorithm, and experiment." International Journal of Advanced Robotic Systems 17, no. 2 (March 1, 2020): 172988142090960. http://dx.doi.org/10.1177/1729881420909603.

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Safe lane changing of the dynamic industrial park and port scenarios with autonomous trucks involves the problem of planning an effective and smooth trajectory. To solve this problem, we propose a new trajectory planning method based on the Dijkstra algorithm, which combines the Dijkstra algorithm with a cost function model and the Bezier curve. The cost function model is established to filter target trajectories to obtain the optimal target trajectory. The third-order Bezier curve is employed to smooth the optimal target trajectory. Road experiments are carried out with an autonomous truck to illustrate the effectiveness and smoothness of the proposed method. Compared with other conventional methods, the improved method can generate a more effective and smoother trajectory in the truck lane change.

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Uppalancha,Kranthi, Bharath. "Optimizing the Robot's Path Using Dijkstra Algorithm." International Journal of Innovative Research in Science, Engineering and Technology 04, no. 06 (June 15, 2015): 4423–30. http://dx.doi.org/10.15680/ijirset.2015.0406050.

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21

Bardi, Martino, and Juan Pablo Maldonado López. "A Dijkstra-Type Algorithm for Dynamic Games." Dynamic Games and Applications 6, no. 3 (May 12, 2015): 263–76. http://dx.doi.org/10.1007/s13235-015-0156-0.

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22

杜, 家康. "Campus Delivery Scheme Based on Dijkstra Algorithm." E-Commerce Letters 07, no. 03 (2018): 38–46. http://dx.doi.org/10.12677/ecl.2018.73006.

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Deepa, G., Priyank Kumar, A. Manimaran, K. Rajakumar, and V. Krishnamoorthy. "Dijkstra Algorithm Application: Shortest Distance between Buildings." International Journal of Engineering & Technology 7, no. 4.10 (October 2, 2018): 974. http://dx.doi.org/10.14419/ijet.v7i4.10.26638.

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The shortest path algorithm is one of the best choices for implementation of data structures. The shortest path (SP) problem involves the problem of finding a suitable path between “two vertices or nodes in a graph” in such a way that the sum of the weights of its component edges is minimal. There are many theories for solving this problem one of the widely used way solution for solving this problem is Dijkstra’s algorithm (DA) which is also widely used in many engineering calculation works also. There are two types of DA one is the basic one and other one is optimized. This paper is focused on the basics one which provides a shortest route between source node and the destination node. Main focus has been kept on keeping the work simple and easy to understand with some basic concepts .Storage space and operational efficiency improvement has been tried to improve.

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Idwan, Sahar, and Wael Etaiwi. "Dijkstra Algorithm Heuristic Approach for Large Graph." Journal of Applied Sciences 11, no. 12 (June 1, 2011): 2255–59. http://dx.doi.org/10.3923/jas.2011.2255.2259.

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Yulianto, Budi. "Teknologi Location Based Service (Global Positioning System) Pada Perangkat Mobile." ComTech: Computer, Mathematics and Engineering Applications 1, no. 1 (June 1, 2010): 61. http://dx.doi.org/10.21512/comtech.v1i1.2168.

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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.

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Wang, Rui, and Na Wang. "Research on Vehicle Path Planning Base on Intelligent Transport System." Applied Mechanics and Materials 513-517 (February 2014): 1822–25. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1822.

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Typical shortest path is Dijkstra algorithm, its time complexity is O (n2). A map of the citys road network has many nodes, if we use the Dijkstra algorithm, the time complexity of the algorithm is too high and the speed of resolution this problem is slow. In order to change this situation, we are discussed from the aspects of algorithm design, puts forward the improved bidirectional search algorithm. Practice has proved that, the improved algorithm can improve the search speed and it suitable for intelligent transportation system.

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Liu, Zhendong, Dongyan Li, Yurong Yang, Xi Chen, Xinrong Lv, and Xiaofeng Li. "Design and Implementation of the Optimization Algorithm in the Layout of Parking Lot Guidance." Wireless Communications and Mobile Computing 2021 (April 12, 2021): 1–6. http://dx.doi.org/10.1155/2021/6639558.

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The information guidance system for parking spaces in large- and medium-sized parking lots is not efficient at present. It tends to be difficult to find an empty parking space in parking lots in big cities. One of the problems is the large amount of calculation in the traditional Dijkstra algorithm. In this paper, an improved Dijkstra algorithm is presented and optimized to find the best parking path with the purpose of looking for the nearest free parking space based on the layout model in parking lot parking guidance. The experiments show that the improved Dijkstra algorithm can find the optimal parking space and the optimal parking path and improve the parking efficiency.

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Keršys, Artūras, and Algirdas Jurkauskas. "SEARCH FOR THE OPTIMAL WAY IN THE NETWORK OF PUBLIC COMMUNICATION." TRANSPORT 17, no. 2 (April 30, 2002): 60–65. http://dx.doi.org/10.3846/16483480.2002.10414013.

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The problem of searching the optimal way in the network of public communication is investigated in the article. The modified Minieka algorithm and designed combined search into depth and Dijkstra algorithm method, operating by the basis of graphs are presented. In order to evaluate practically the efficiency and applicability of algorithms experimental calculating of route search in the model of public transport communication network has been made. Public transport network changed in to graph is a real public transport network segment in Kaunas. Having compared their efficiency (memory size and calculating time) it has been proved that both methods might be applied to solve the problem as well as be integrated into the prediction models of communication processes. The combined depth-first search and Dijkstra algorithm method are better.

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Alwan, Nuha A. S. "Performance Analysis of Dijkstra-Based Weighted Sum Minimization Routing Algorithm for Wireless Mesh Networks." Modelling and Simulation in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/658408.

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Multiobjective optimization methods for routing in static wireless mesh networks (WMNs), with more than one QoS measure to be optimized, are highly challenging. To optimize the performance for a given end-to-end route in a static network, the most common metrics that need to be optimized or bounded are the path capacity and the end-to-end delay. In this work, we focus on combining desirable properties of these two metrics by minimizing a weighted metrics sum via a Dijkstra-based algorithm. The approach is directed towards fast convergence rather than optimality. It is shown that the resulting algorithm provides more satisfactory results than simple Dijkstra-based pruning algorithms in terms of simultaneously achieving high capacity and small delay. The effect of changing the weighting factor on the proposed algorithm performance is investigated.

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Tan, Yong, and Dan Wu. "Research on Optimization of Distribution Routes for Fresh Agricultural Products Based on Dijkstra Algorithm." Applied Mechanics and Materials 336-338 (July 2013): 2500–2503. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.2500.

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According to the specialty of fresh agricultural products, a delivery model was established. The model consists of single distribution center and multiple demand points. The integrated cost which consists of transport cost and time cost was taken as the optimization objective. It is used as weight in classic Dijkstra algorithm instead of distance. We also used a case study to illustrate saving method and classic Dijkstra algorithm with integrated cost. The comparison was conducted by calculating the integrated cost of optimal routes separately. Following the comparison, we draw a conclusion that in the field of fresh agricultural products distribution, classic Dijkstra algorithm which takes integrated cost as optimization objective is superior to the saving method in which distance is the optimization objective.

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Mubarok, Rofiq, Dwi Verdy Firmansyah, Dheny Haryanto, Noor Pratama Apriyanto, Umniyatul Mahmudah, and Iswanto Iswanto. "Motorcycle-Security using Position Searching Algorithm Based on Hybrid Fuzzy-Dijkstra." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 2 (August 1, 2016): 468. http://dx.doi.org/10.11591/ijeecs.v3.i2.pp468-474.

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<strong>Motorcycle safety system has been provided by the manufacturer in the form of a handlebar lock and electrical key equipped with alarms. Keys provided by the manufacturers sometimes fail in securing a motorcycle. In addition the safety system does not provide position information of the stolen motorcycle to the owner. With these problems, the paper presents safety locked motorcycle equipped with artificial intelligence algorithms. Artificial intelligence algorithm is used to find and detect the location of the motorcycle using the shortest path algorithm. This paper applies search algorithm using Dijkstra algorithm where the algorithm is used to make the decision to get the location of the motorcycle. By using the algorithm, the location of the motorcycle can be detected but it is not able to find the shortest path needed. Therefore, this paper describes the modification of Dijkstra algorithm by adding a Fuzzy algorithm that is used for the weight values in decision making, so that it can pursue to find the shortest path.</strong>

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Cadieux, Nicolas, Margaret Kalacska, Oliver T. Coomes, Mari Tanaka, and Yoshito Takasaki. "A Python Algorithm for Shortest-Path River Network Distance Calculations Considering River Flow Direction." Data 5, no. 1 (January 16, 2020): 8. http://dx.doi.org/10.3390/data5010008.

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Vector based shortest path analysis in geographic information system (GIS) is well established for road networks. Even though these network algorithms can be applied to river layers, they do not generally consider the direction of flow. This paper presents a Python 3.7 program (upstream_downstream_shortests_path_dijkstra.py) that was specifically developed for river networks. It implements multiple single-source (one to one) weighted Dijkstra shortest path calculations, on a list of provided source and target nodes, and returns the route geometry, the total distance between each source and target node, and the total upstream and downstream distances for each shortest path. The end result is similar to what would be obtained by an “all-pairs” weighted Dijkstra shortest path algorithm. Contrary to an “all-pairs” Dijkstra, the algorithm only operates on the source and target nodes that were specified by the user and not on all of the nodes contained within the graph. For efficiency, only the upper distance matrix is returned (e.g., distance from node A to node B), while the lower distance matrix (e.g., distance from nodes B to A) is not. The program is intended to be used in a multiprocessor environment and relies on Python’s multiprocessing package.

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Gao, Xiu Li, Tian Jun Hu, and Jia Zheng. "Research on Dynamic Path Selection Improved Dijkstra Algorithm." Advanced Materials Research 1006-1007 (August 2014): 1121–24. http://dx.doi.org/10.4028/www.scientific.net/amr.1006-1007.1121.

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Dynamic path selection algorithm is one of the most important researches in Intelligent Transportation System (ITS). After comparing in this article, we select Dijkstra algorithm as the optimal path algorithm. The traditional algorithm applies only to the static road network, the improved algorithm obtained optimal path planning program in the dynamic path selection. Finally, the combination of a numerical example, the improved algorithm for real-time, dynamic, effectiveness is verified through computer simulation. The accuracy of the prediction of the traffic flow plays a key role in the path planning, and the fusion forecast information dynamic path selection problem has important practical significance.

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Karami, Fateme, and Ehsan Akhtarkavan. "Improving OSPF Protocol based Latency : A new algorithm based on Dijkstra by using OSPF existing Metrics in SDN networks." Ciência e Natura 37 (December 19, 2015): 344. http://dx.doi.org/10.5902/2179460x20793.

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SDN (software defined networking)-based networks may be defined as a new generation of networks using virtual layers and switches and central controller which try to handle a few controlling and managerial tasks of switches and rotors of networks in upper layers on a software basis. In fact, it reduced dependence to hardware and increases software capabilities. These networks face challenges such as quality of relationship between controller and devices existing in the network and delay in network that is subject of this thesis. According to the applied researches, one of offered solutions for reduction of delay is using path finding algorithms. Rotors’ task is transfer of information. Algorithms must be implemented on these rotors to choose the best path for data transfer in the network. Path finding table is used in rotor. According to the data available in path finding table, the best path is found. Each path finder must have complete information of network’s communication infrastructure and calculate and identify all other paths of communications between them and their costs. Later, data collection forms the data structure related to network infrastructure graph. In these conditions, to find the best path between path finders, the shortest path algorithms (SPT) are used such as Dijkstra. Since rotors receive the sent update massages due to network changes, path finding table amends itself and identifies the new probability path. Selection of best path is made by massages metric. Upon processor fastening and hardware cheapening, a standard protocol in the name of OSPF was presented that manufactured by CISCO, particularly in a network that its equipment are not necessarily made by CISCO is based on Dijkstra and uses cost and band broadness as metric, transfer the data related to connected network and rotors connected to network between adjacent rotors and records all of its information in the table. Later, Dijkstra's algorithm is implemented and the best paths led to different destinations are inserted in the path finding table. The objective of this study was presenting an algorithm based on Dijkstra there in addition to cost Metric, another metric to be used that highly reduces traffic in the network and improves delay time in the network.

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Singal, Pooja, and R. S. Chhillar R.S.Chhillar. "Dijkstra Shortest Path Algorithm using Global Position System." International Journal of Computer Applications 101, no. 6 (September 18, 2014): 12–18. http://dx.doi.org/10.5120/17690-8654.

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Hossain, Md Sabir, Nayan Das, Muhammad Kamrul Hossain Patwary, and Md Al-Hasan. "Finding the Nearest Blood Donors using Dijkstra Algorithm." SISFORMA 5, no. 2 (January 21, 2019): 40. http://dx.doi.org/10.24167/sisforma.v5i2.1709.

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Now-a-days frequent mishaps like the road accident or other life-risking accident leading to operational emergencies are increasing day by day and the blood donor for such victims or patients are very hard to find in a short period. Sometimes it is really tough to collect the blood of the same group from the relatives of a patient in dying moments. The main objective of this work is to make a connection with these two groups who are in need of blood and who are willing to donate. We have determined the shortest distance between blood seeker and blood donors using the Dijkstra Algorithm. Anybody can contact the nearest blood donor of any group in a particular area quickly. By implementing this idea, the harassment of the victim can be lessened and so many lives can be saved.

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Silveira, Pedro, Ângelo Palos Teixeira, and Carlos Guedes Soares. "AIS Based Shipping Routes Using the Dijkstra Algorithm." TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation 13, no. 3 (2019): 565–71. http://dx.doi.org/10.12716/1001.13.03.11.

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Moo Mena, Francisco, Rafael Hernandez Ucan, Victor Uc Cetina, and Francisco Madera Ramirez. "Web service composition using the bidirectional Dijkstra algorithm." IEEE Latin America Transactions 14, no. 5 (May 2016): 2522–28. http://dx.doi.org/10.1109/tla.2016.7530454.

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Sun, Yinghui, Ming Fang, and Yixin Su. "AGV Path Planning based on Improved Dijkstra Algorithm." Journal of Physics: Conference Series 1746 (January 2021): 012052. http://dx.doi.org/10.1088/1742-6596/1746/1/012052.

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Cai, Junpeng, Dewang Chen, Shixiong Jiang, and Weijing Pan. "Dynamic-Area-Based Shortest-Path Algorithm for Intelligent Charging Guidance of Electric Vehicles." Sustainability 12, no. 18 (September 8, 2020): 7343. http://dx.doi.org/10.3390/su12187343.

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With the increasing popularization and competition of electric vehicles (EVs), EV users often have anxiety on their trip to find better charging stations with less travel distance. An intelligent charging guidance strategy and two algorithms were proposed to alleviate this problem. First, based on the next destination of EV users’ trip, the strategy established a dynamic-area model to match charging stations with users’ travel demand intelligently. In the dynamic area, the Dijkstra algorithm is used to find the charging station with the shortest trip. Then, the area extension algorithm and the charging station attribution algorithm were developed to improve the robustness of the dynamic area. The two algorithms can automatically adjust the area size according to the number of charging stations in the dynamic area to reduce the number of nodes traversed by the Dijkstra algorithm. Finally, simulation examples were used to verify the effectiveness of the proposed model and algorithms. The results showed that the proposed intelligent charging guidance strategy can meet the travel demand of users. It is a promising technique in smart cities to find better travel trips with less travel distance and less computed time.

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Setiawan, Jodi, Rezy S. Prakoso, and Kristien Margi Suryaningrum. "PENENTUAN RUTE TERPENDEK MENUJU PUSAT PERBELANJAAN DI JAKARTA MENGGUNAKAN ALGORITMA DIJKSTRA." Jurnal Ilmiah Matrik 21, no. 3 (December 18, 2019): 156–65. http://dx.doi.org/10.33557/jurnalmatrik.v21i3.715.

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Abstract : Shopping centers are easy to find in big cities like Jakarta and because there are too many times people are often confused which one to go to, not to mention if people from outside Jakarta come and want to visit a shopping center. The problem to choose a shopping center that encourages researchers to conduct a study to develop applications to find the nearest shopping center using the Dijkstra algorithm that can be used on smartphones in order to make it easier to find and find shopping centers around users. The application was designed using flowchart and UML and was made using Android Studio with the help of the Google Maps API to display maps, display pins, find and display the nearest route using latitude and longitude from Google Maps. Algorithm to calculate and determine the route that must be traversed using the Dijkstra algorithm. The accuracy of the calculation results using the Dijkstra algorithm reaches 93%

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Tie, Chun Hua, and Yan Chun Shen. "An Improved Graph-Based Depth-First Algorithm and Dijkstra Algorithm Program of Police Patrol." Advanced Materials Research 433-440 (January 2012): 4135–41. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4135.

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The urban road network is abstracted as a directed graph in this paper，according to the theory of graph theory. It uses depth-first traversal algorithm of graph，and combining with Dijkstra shortest path algorithm，futhermore ,these two algorithms are improved，so that , the model of this regional division are built which on city roads for patrol’s police Alarm practical speed and distance as the verification conditions，we propose an efficient program for the city police patrol.

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Liu, Yan, Ying Ju Li, and Yan Xiao Zhang. "Study of the Logistics Transportation Vehicle Terminal Path Optimization and Algorithm Based on GIS." Applied Mechanics and Materials 644-650 (September 2014): 2249–52. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2249.

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Based on feasibility and rationality, the path of the distribution centers, cargo terminal and receiving point as the optimized object.Using the Dijkstra algorithm and to improve it,set up customer logistics cost minimum as the target of route choice model;Using the improved Dijkstra algorithm greatly improves the operation speed,especially in the cross area for the shortest path,division graph method has very big enhancement to the time complexity of the algorithm ,enable the customer logistics total cost minimum.Therefore, route choice model can accurately describe the logistics distribution problem.

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Wu, Shao Kai, and Jing Lei Zhang. "Optimal Path Planning of Beidou Navigation System Based on Dijkstra Algorithm." Applied Mechanics and Materials 599-601 (August 2014): 1584–87. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1584.

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The optimal path planning plays an important role in the satellite navigation system. This paper uses the Dijkstra algorithm, which gives a shortest path first, to find a more effective travel decision. The decision combines the Dijkstra algorithm with the real-time traffic information and gives an effective travel plan. This system is developed under C# environment, achieves the goals of travel path planning and traffic guidance, and can supply a variety of travel plan to the traveler according to the difference influence factors.

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Handy Permana, Silvester Dian, Ketut Bayu Yogha Bintoro, Budi Arifitama, and Ade Syahputra. "Comparative Analysis of Pathfinding Algorithms A *, Dijkstra, and BFS on Maze Runner Game." IJISTECH (International Journal Of Information System & Technology) 1, no. 2 (May 25, 2018): 1. http://dx.doi.org/10.30645/ijistech.v1i2.7.

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Maze Runner game is a game that requires pathfinding algorithm to get to the destination with the shortest path. This algorithm is used in an NPC that will move from start node to destination node. However, the use of incorrect algorithms can affect the length of the computing process to find the shortest path. The longer the computing process, the longer the players have to wait. This study compared pathfinding algorithms A *, Dijkstra, and Breadth First Search (BFS) in the Maze Runner game. Comparison process of these algorithms was conducted by replacing the algorithm in the game by measuring the process time, the length of the path, and the numbers of block played in the existing computing process. The results of this study recommend which algorithm is suitable to be applied in Maze Runner Game.

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Zhi, Tan, and Zhang Hui. "An Improved Ant Colony Routing Algorithm for WSNs." Journal of Sensors 2015 (2015): 1–4. http://dx.doi.org/10.1155/2015/438290.

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Ant colony algorithm is a classical routing algorithm. And it are used in a variety of application because it is economic and self-organized. However, the routing algorithm will expend huge amounts of energy at the beginning. In the paper, based on the idea of Dijkstra algorithm, the improved ant colony algorithm was proposed to balance the energy consumption of networks. Through simulation and comparison with basic ant colony algorithms, it is obvious that improved algorithm can effectively balance energy consumption and extend the lifetime of WSNs.

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Cheng, Ningyi, Zhiqian Liu, and Yuqi Li. "Path Planning Algorithm of Dijkstra-Based Intelligent Aircraft under Multiple Constraints." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 38, no. 6 (December 2020): 1284–90. http://dx.doi.org/10.1051/jnwpu/20203861284.

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Aiming at the rapid planning of the optimal flight path of the intelligent aircraft, considering the error constraints and correction probability constraints, a model for intelligent aircraft path planning under multiple constraints is constructed, and a global search algorithm based on Dijkstra algorithm is proposed to solve the model. By calculating the residual error and restricts flight distance, the basic Dijkstra algorithm is improved to make it more adaptable to solve the path planning under multiple constraints. At the same time, simulation experiment is conducted with the optimal goal of the shortest track length and satisfying the error constraints. The experimental results show that the aircraft passed a total of 18 correction points when it reached the destination. The total track length was 144 287.932 m, the vertical position error was 17.254 units, and the horizontal position error was 6.420 units. The results meet the error requirements. The results show that the intelligent aircraft path planning model and Dijkstra-based global search algorithm with multiple constraints are reasonable in solving such problems.

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Fang, Wang, Jian Guo Zhang, and Hai Yan Song. "Global and Local Path Planning on Robotic Wheelchair Based on Multi-Sensor Information Fusion." Advanced Materials Research 655-657 (January 2013): 1145–48. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.1145.

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This paper represented the method of obstacle avoidance for robotic wheelchair based on the multi-sensor information fusion. The installing angle of sensor was analyzed. Path planning was discussed in global or local environment separately. Dijkstra algorithm and fuzzy control algorithm were proposed to solve the problem of global and local path tracking. The simulation had provided an easy-used method for designing and validating the algorithms.

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Lopez-Pavon, Cristina, Sandra Sendra, and Juan F. Valenzuela-Valdes. "Evaluation of CupCarbon Network Simulator for Wireless Sensor Networks." Network Protocols and Algorithms 10, no. 2 (June 28, 2018): 1. http://dx.doi.org/10.5296/npa.v10i2.13201.

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Wireless sensor networks are a technology in full evolution with great future and a huge quantity of applications. This document lists some of the limitations existing in WSN networks. In addition, several existing techniques are collected to maximize the network's lifetime, demonstrating that efficient use of energy is very important to achieve this goal. Due to the importance of knowing the behaviour of this type of network before its launch, a comparative is established for the options offered by the WSN network simulators available in the market, compared to those offered by CupCarbon. The objective of this project is the evaluation of the CupCarbon simulator through the implementation of an algorithm that aims to maximize the life time of the network, as well as collecting the results offered by this algorithm. In this way, a Dijkstra routing algorithm is developed whose selection of routes depends on the battery level contained in the nodes that constitute the network. This algorithm is referred as dynamic Dijkstra in the present document. To achieve the objectives described, we pretend to simulate the dynamic Dijkstra in CupCarbon, for this aim, the source code is modified, since it is a free code tool. As a result, it is possible to create the original Dijkstra, but certain problems are presented, to develop the part that depends on the energy, related to the functionalities offered by CupCarbon. As an alternative to determine the results associated to the created algorithm, theoretical analyses are accomplished. Consequently, it is concluded that the evaluation of CupCarbon is not satisfactory enough, while the algorithm created maximizes the network's lifetime.

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Umar, Rusydi, Anton Yudhana, and Andi Prayudi. "Analisis Perbandingan Algoritma Djikstra, A-Star, dan Floyd Warshall dalam Pencarian Rute Terdekat pada Objek Wisata Kabupaten Dompu." Jurnal Teknologi Informasi dan Ilmu Komputer 8, no. 2 (March 25, 2021): 227. http://dx.doi.org/10.25126/jtiik.0812866.

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<p>Diera industri 4.0, penggunaan peta tidak lagi berbentuk lembaran ataupun buku. Kini terdapat sebuah layananan peta digital yaitu <em>platform</em> Leafleat.js, yang memudahkan penggunanya untuk mendapatkan informasi rute dari objek ke objek lainnya dan mencari lokasi hampir diseluruh dunia. Pada penelitian ini menggunakan objek yang <em>real </em>yaitu menampilkan lokasi sebenarnya menggunakan <em>platform</em> Leaflet.js dan parameter yang berbeda, dari hal tersebut penelitian ini akan membandingkan kinerja dari Algoritma <em>Dijkstra</em>, A* dan <em>Floyd Warshall</em> untuk menentukan waktu proses pencarian rute terdekat dari objek wisata ke objek wisata lain menggunakan bahasa pemograman PHP. Hasil pengujian program didapatkan jarak dan rute yang sama serta rata-rata waktu proses program yang berbeda. Waktu proses algoritma <em>Dijkstra</em> sebesar 0,0060 detik, algoritma A* sebesar 0,0067 dan algoritma <em>Floyd Warshall</em> sebesar 0,0433 detik. Berdasarkan hasil tersebut bahwa algoritma <em>Dijkstra</em> lebih unggul dalam proses pencarian rute.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>In the industrial era 4.0, the use of maps is no longer made of book sheets. Now a digital map service is available, the Leafleat.js platform, which provides users to get route information from other attractions and find locations that have been saved by the world. In this study using real objects that display the actual location using the Leaflet.js platform and different parameters, from this study will compare the performance of the Dijkstra, A * and Floyd Warshall Algorithms for the process of finding other tourist information using the PHP programming language. The results of testing the program obtained the same distance and route with different program processing time. Dijkstra algorithm processing time is 0.0060 seconds, A* algorithm is 0.0067 and Floyd Warshall algorithm is 0.0433 seconds. Based on these results, Dijkstra is superior in the route search process.</em></p><p><em><strong><br /></strong></em></p>

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