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Статті в журналах з теми "Shortest path search in network"

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Schneck, Arne, and Klaus Nökel. "Accelerating Traffic Assignment with Customizable Contraction Hierarchies." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 1 (2020): 188–96. http://dx.doi.org/10.1177/0361198119898455.

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In many algorithms for traffic assignment, the most time-consuming step is shortest path search between all O–D pairs. Almost unnoticed by the transport modeling community, there has been an enormous amount of research on acceleration techniques for the shortest path problem in road networks in the past decade. These techniques usually divide the problem into a relatively expensive preprocessing phase and a significantly accelerated search phase. In this paper, the recently developed customizable contraction hierarchies are used for both shortest path search and network loading in the bi-conju
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Guo, Ya Fei, Zheng Qin, Rong Hua Guo, and Lei Ji. "SH: A Novel Method for the Dynamic and Shortest Path Problem." Advanced Materials Research 129-131 (August 2010): 1013–17. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.1013.

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For the dynamic and shortest path problem, a novel algorithm SH(simulate human) is designed by simulating the process of our searching path in real life. The algorithm adopts the idea of heuristic search and integrates with the ant colony algorithm, in which the saved current path, the idea of “ask once every junction”, the bypassing barrier search and other some related definitions are proposed, as well as the ant colony algorithm is improved, so as to find the better solution and reduce the searching time. The experimental results show that the algorithm runs better than other existing metho
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Yuan, C., and B. Malone. "Learning Optimal Bayesian Networks: A Shortest Path Perspective." Journal of Artificial Intelligence Research 48 (October 16, 2013): 23–65. http://dx.doi.org/10.1613/jair.4039.

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In this paper, learning a Bayesian network structure that optimizes a scoring function for a given dataset is viewed as a shortest path problem in an implicit state-space search graph. This perspective highlights the importance of two research issues: the development of search strategies for solving the shortest path problem, and the design of heuristic functions for guiding the search. This paper introduces several techniques for addressing the issues. One is an A* search algorithm that learns an optimal Bayesian network structure by only searching the most promising part of the solution spac
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LONG, Ke-jun, Lee D. HAN, and Sai-zheng WANG. "Shortest path search in road network with incomplete information." Journal of Computer Applications 31, no. 3 (2011): 651–53. http://dx.doi.org/10.3724/sp.j.1087.2011.00651.

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Bilò, Davide, Keerti Choudhary, Sarel Cohen, Tobias Friedrich, and Martin Schirneck. "Efficient Fault-Tolerant Search by Fast Indexing of Subnetworks." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 25 (2025): 26463–71. https://doi.org/10.1609/aaai.v39i25.34846.

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We design sensitivity oracles for error-prone networks. For a network problem Π, the data structure preprocesses a network G=(V,E) and sensitivity parameter f such that, for any set F of up to f link or node failures, it can report the solution of Π in G-F. We study three network problems Π. - L-Hop Shortest Path: Given s,t in V, is there a shortest s-t-path in G-F with at most L links? - k-Path: Does G-F contain a simple path with k links? - k-Clique: Does G-F contain a clique of k nodes? Our main technical contribution is a new construction of (L,f)-replacement path coverings ((L,f)-RPC) in
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Hui, Shumin, and Yuefei Wang. "Research on the Social Network Search Strategy from the Viewpoint of Comprehensive Influence Maximization." Journal of Advanced Computational Intelligence and Intelligent Informatics 27, no. 6 (2023): 1037–44. http://dx.doi.org/10.20965/jaciii.2023.p1037.

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Considering that social network provides a channel for nodes to exchange information, resources, and interests, the fundamental task of social network search is to find the best path from the source node to the target node. The search strategy based on the shortest path principle ignores the strength and direction of the social relationship between nodes in the social network, and ignores the difference of influence between nodes, so that the search results cannot meet the needs of searchers. Considering the important role of the influence of nodes and the influence intensity between nodes in
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Wang, Zhengdong, Yifeixue Yang, Ziyi Huang, et al. "Exploring the transmission of cognitive task information through optimal brain pathways." PLOS Computational Biology 21, no. 3 (2025): e1012870. https://doi.org/10.1371/journal.pcbi.1012870.

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Understanding the large-scale information processing that underlies complex human cognition is the central goal of cognitive neuroscience. While emerging activity flow models demonstrate that cognitive task information is transferred by interregional functional or structural connectivity, graph-theory-based models typically assume that neural communication occurs via the shortest path of brain networks. However, whether the shortest path is the optimal route for empirical cognitive information transmission remains unclear. Based on a large-scale activity flow mapping framework, we found that t
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Lu, Pan, Chuanfang Jing, and Xiaorong Zhu. "GraphSAGE-Based Multi-Path Reliable Routing Algorithm for Wireless Mesh Networks." Processes 11, no. 4 (2023): 1255. http://dx.doi.org/10.3390/pr11041255.

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Wireless mesh networks (WMN) promise to be an effective way to solve the “last mile” access problem on the Internet of Things (IoT) and the key to next-generation wireless networks. The current routing algorithms of WMN are difficult to adapt to complex environments and guarantee the reliable transmission of services. Therefore, this paper proposes a reliable routing algorithm that combines the improved breadth-first search and a graph neural network, namely GraphSAGE. The algorithm consists of two parts: (1) A multi-path routing algorithm based on the improved breadth-first search. This algor
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杨, 颖. "The Shortest Path Search of Radio Broadcast Model Based on Path Network." Computer Science and Application 08, no. 12 (2018): 1798–803. http://dx.doi.org/10.12677/csa.2018.812199.

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Zhang, Shuijian, Xuejun Liu, and Meizhen Wang. "A novel ant colony optimization algorithm for the shortest-path problem in traffic networks." Filomat 32, no. 5 (2018): 1619–28. http://dx.doi.org/10.2298/fil1805619z.

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The Ant Colony Optimization (ACO) algorithm is a metaheuristic nature-inspired technique for solving various combinatorial optimization problems. The shortest-path problem is an important combinatorial optimization problem in network optimization. In this paper, a novel algorithm based on ACO to solve the single-pair shortest-path problem in traffic networks is introduced. In this algorithm, a new strategy is developed to find the best solution in a local search, by which the ants seek the shortest path using both a pheromone-trail-following mechanism and an orientation-guidance mechanism. A n
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Дисертації з теми "Shortest path search in network"

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Holmgren, Johan. "Efficient Updating Shortest Path Calculations for Traffic Assignment." Thesis, Linköping University, Department of Mathematics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2573.

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<p>Traffic planning in a modern congested society is an important and time consuming procedure. Finding fast algorithms for solving traffic problems is therefore of great interest for traffic planners allover the world. </p><p>This thesis concerns solving the fixed demand traffic assignment problem (TAP) on a number of different transportation test networks. TAP is solved using the Frank-Wolfe algorithm and the shortest path problems that arise as subproblems to the Frank-Wolfe algorithm are solved using the network simplex algorithm. We evaluate how a number of existing pricing strategies to
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Hong, Chyi-Fu. "O(n) planar network shortest path algorithm." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/24841.

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Hojnacki, Susan M. "Optimizing algorithms for shortest path analysis /." Online version of thesis, 1991. http://hdl.handle.net/1850/11143.

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Hua, Liyan. "Shortest Path - Capacitated Maximum Covering Problems." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275477591.

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Montes, Anel A. "Network shortest path application for optimum track ship routing." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://handle.dtic.mil/100.2/ADA435601.

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Ruan, Ning. "Network Backbone with Applications in Reachability and Shortest Path Computation." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1334516240.

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Allen, Andrea J. "Average Shortest Path Length in a Novel Small-World Network." Oberlin College Honors Theses / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1516362622694547.

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Ahmed, Mahad A. (Mahad Mohamed) 1973 Carleton University Dissertation Engineering Systems and Computer. "Performance analysis and improvement of the Open Shortest Path First routing protocol." Ottawa.:, 1999.

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Перепеліцин, Сергій Олександрович, та Sergiy Perepelitsyn. "Технологія налаштовування радіомережі в умовах завад інтеграцією маршрутизації та самонавчання". Thesis, Національний авіаційний університет, 2021. https://er.nau.edu.ua/handle/NAU/49767.

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Дисертаційна робота присвячене розв'язання науково-технічної задачі зі створення інформаційної технології моделювання ефективного контролю за топологією однорангової мобільної радіомережі, що само налагоджується, тактичного рівня й управління зміною показників її функціонування в умовах впливу радіоперешкод та радіоелектронної протидії (РЕБ). У дисертаційній роботі вперше запропоновано нова топологія, що відрізняється від відомих тим, що включає елементи навчання поведінки мережі в умовах перешкод. Введені нові процеси інтелектуальної системи керування вузлом мобільної радіомережі: пошукова
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Mohiuddin, Mohammed Aijaz. "Engineering Nature-Inspired Heuristics for the Open Shortest Path First Weight Setting Problem." Thesis, University of Pretoria, 2018. http://hdl.handle.net/2263/65988.

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In the thesis of “Mohammed Aijaz Mohiuddin”, Engineering Nature-Inspired Heuristics for the Open Shortest Path First Weight Setting Problem, nature inspired heuristics were developed. Besides the existing two objectives, namely maximum utilization and the number of congested links, a third objective namely the number of unused links was used to formulate the fuzzy based objective function for the OSPFWS problem. The idea was to make use unused network links if any. Furthermore, a hybrid fuzzy based evolutionary Particle Swarm Optimization (FEPSO) algorithm was designed that harnessed evolution
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Книги з теми "Shortest path search in network"

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Shing, Man-Tak. Persistence search -- a new search strategy for the dynamic shortest path problem. Naval Postgraduate School, 1991.

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2

Jenkins, Kevin Dean. The shortest path problem in the plane with obstacles: A graph modeling approach to producing finite search lists of homotopy classes. Naval Postgraduate School, 1991.

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Newman, Mark. Computer algorithms. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805090.003.0008.

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This chapter introduces some of the fundamental concepts of numerical network calculations. The chapter starts with a discussion of basic concepts of computational complexity and data structures for storing network data, then progresses to the description and analysis of algorithms for a range of network calculations: breadth-first search and its use for calculating shortest paths, shortest distances, components, closeness, and betweenness; Dijkstra's algorithm for shortest paths and distances on weighted networks; and the augmenting path algorithm for calculating maximum flows, minimum cut se
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Cisco OSPF Command and Configuration Handbook (paperback). Cisco Press, 2008.

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5

Valadas, Rui. OSPF and IS-IS: From Link State Routing Principles to Technologies. Taylor & Francis Group, 2019.

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Valadas, Rui. OSPF and IS-IS: From Link State Routing Principles to Technologies. Taylor & Francis Group, 2019.

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Valadas, Rui. OSPF and IS-IS: From Link State Routing Principles to Technologies. Taylor & Francis Group, 2019.

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Valadas, Rui. Ospf and Is-Is. Taylor & Francis Group, 2020.

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OSPF and IS-IS: From Link State Routing Principles to Technologies. Taylor & Francis Group, 2019.

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OSPF and IS-IS: From Link State Routing Principles to Technologies. Taylor & Francis Group, 2019.

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Частини книг з теми "Shortest path search in network"

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Schmid, Stefan, Nicolas Schnepf, and Jiří Srba. "Resilient Capacity-Aware Routing." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_22.

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AbstractTo ensure a high availability, communication networks provide resilient routing mechanisms that quickly change routes upon failures. However, a fundamental algorithmic question underlying such mechanisms is hardly understood: how to verify whether a given network reroutes flows along feasible paths, without violating capacity constraints, for up to k link failures? We chart the algorithmic complexity landscape of resilient routing under link failures, considering shortest path routing based on link weights as e.g. deployed in the ECMP protocol. We study two models: a pessimistic model
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Sharaiha, Yazid M., and Richard Thaiss. "Guided Search for the Shortest Path on Transportation Networks." In Meta-Heuristics. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1361-8_8.

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Król, Dariusz, and Łukasz Popiela. "Modelling Shortest Path Search Techniques by Colonies of Cooperating Agents." In Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04441-0_58.

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Febbraro, A. Di, and S. Sacone. "Dynamic search for shortest multimodal paths in a transportation network." In System Modelling and Optimization. Springer US, 1996. http://dx.doi.org/10.1007/978-0-387-34897-1_72.

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Eiselt, H. A., and C. L. Sandblom. "Shortest Path Problems." In Integer Programming and Network Models. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04197-0_13.

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Hamacher, Horst W., and Kathrin Klamroth. "Shortest Path Problems." In Lineare und Netzwerk-Optimierung / Linear and Network-Optimization. Vieweg+Teubner Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-91579-5_6.

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Howser, Gerry. "Shortest Path Through the Network." In Computer Networks and the Internet. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34496-2_13.

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Shirabe, Takeshi. "Shortest Path Search from a Physical Perspective." In Spatial Information Theory. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11556114_6.

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Ahmad, Amreen, Tanvir Ahmad, and Harsh Vijay. "Shortest Path Algorithms for Social Network Strengths." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3153-3_35.

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Tan, Guozhen, Xiaojun Han, and Wen Gao. "Network-Tree Model and Shortest Path Algorithm." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44863-2_53.

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Тези доповідей конференцій з теми "Shortest path search in network"

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Ho, Yang, Armida Carbajal, Leonardo Escamilla, and Ali Pinar. "Neuromorphic Monte Carlo Tree Search Methods for Shortest Path Interdiction." In 2024 International Conference on Neuromorphic Systems (ICONS). IEEE, 2024. https://doi.org/10.1109/icons62911.2024.00053.

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Zhang, Jianwei, Xin Li, Bowen Cui, and Chunling Yang. "Poster: An FPTAS for Shortest-Longest Path Problem." In 2024 IEEE 32nd International Conference on Network Protocols (ICNP). IEEE, 2024. https://doi.org/10.1109/icnp61940.2024.10858508.

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Narang, Mehak, and Ziaul Hossain. "Comparative Analysis of Shortest-Path Algorithms in Network Routing." In 2025 10th International Conference on Computer and Communication System (ICCCS). IEEE, 2025. https://doi.org/10.1109/icccs65393.2025.11069970.

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Liu, Songwei, Lilla Beke, and Jun Chen. "Heuristic Initialisation based on Graph Structures for Shortest Path Search on Multi-objective Multigraphs." In 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025. https://doi.org/10.1109/cec65147.2025.11042998.

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Sumarudin, A., Nana Sutisna, Infall Syafalni, Bambang Riyanto Trilaksono, and Trio Adiono. "Optimizing Deep Q-Network for Shortest Path Computation of Mobile Robot Agents." In 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2024. https://doi.org/10.1109/apsipaasc63619.2025.10849184.

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Jun, Kang, Wu Zihao, and Wang Qianqian. "Time-constrained shortest path search algorithm for urban road network." In 2023 7th International Conference on Transportation Information and Safety (ICTIS). IEEE, 2023. http://dx.doi.org/10.1109/ictis60134.2023.10243896.

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Dhrubajyoti, Ghosh, Majumder Saibal, and Pal Anita. "Searching Shortest Path in a Network Using Modified A* Search Algorithm." In AASRI International Conference on Industrial Electronics and Applications (IEA 2015). Atlantis Press, 2015. http://dx.doi.org/10.2991/iea-15.2015.70.

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Rankin, Arturo L., and Carl D. Crane. "A Multi-Purpose Off-Line Path Planner Based on an A* Search Algorithm." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/mech-1134.

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Abstract Efficient navigation of an autonomous mobile robot through a well-defined environment requires the ability of the robot to plan paths. An efficient and reliable planar off-line path planner has been developed that is based on the A* search method. Using this method, two types of planning are accomplished. The first uses a map of all known obstacles to determine the shortest-distance path from a start to goal configuration. The second determines the shortest path along a network of predefined roads. For the most complicated environment of obstacles and roads, a near-optimal piecewise-l
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Lu, Zheng, Yunhe Feng, and Qing Cao. "Decentralized Search for Shortest Path Approximation in Large-Scale Complex Networks." In 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2017. http://dx.doi.org/10.1109/cloudcom.2017.36.

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Yue, Hao, and Chunfu Shao. "Study on Distributed and Parallel Search Strategy of Shortest Path in Urban Road Network." In Third International Conference on Natural Computation (ICNC 2007) Vol V. IEEE, 2007. http://dx.doi.org/10.1109/icnc.2007.689.

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Звіти організацій з теми "Shortest path search in network"

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Shing, Man-Tak, and Michael M. Mayer. Persistence Search - A New Search Strategy for the Dynamic Shortest Path Problem. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada238741.

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Striuk, Andrii, Olena Rybalchenko, and Svitlana Bilashenko. Development and Using of a Virtual Laboratory to Study the Graph Algorithms for Bachelors of Software Engineering. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4462.

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The paper presents an analysis of the importance of studying graph algorithms, the reasons for the need to implement this project and its subsequent use. The existing analogues analysis is carried out, due to which a list of advantages and disadvantages is formed and taken into account in developing the virtual laboratory. A web application is created that clearly illustrates the work of graph algorithms, such as Depth-First Search, Dijkstra’s Shortest Path, Floyd- Warshall, Kruskal Minimum Cost Spanning Tree Algorithm. A simple and user- friendly interface is developed and it is supported by
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