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Journal articles on the topic 'Minimum bottleneck spanning tree'

Author: Grafiati

Published: 24 April 2022

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1

Shi, Xueyu, Bo Zeng, and Oleg A. Prokopyev. "On bilevel minimum and bottleneck spanning tree problems." Networks 74, no. 3 (2019): 251–73. http://dx.doi.org/10.1002/net.21881.

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2

Andersen, Patrick J., and Charl J. Ras. "Minimum bottleneck spanning trees with degree bounds." Networks 68, no. 4 (2016): 302–14. http://dx.doi.org/10.1002/net.21710.

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3

Zhang, Binwu, Jianzhong Zhang, and Yong He. "Constrained Inverse Minimum Spanning Tree Problems under the Bottleneck-Type Hamming Distance." Journal of Global Optimization 34, no. 3 (2006): 467–74. http://dx.doi.org/10.1007/s10898-005-6470-0.

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4

Andersen, Patrick J., and Charl J. Ras. "Algorithms for Euclidean Degree Bounded Spanning Tree Problems." International Journal of Computational Geometry & Applications 29, no. 02 (2019): 121–60. http://dx.doi.org/10.1142/s0218195919500031.

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Given a set of points in the Euclidean plane, the Euclidean [Formula: see text]-minimum spanning tree ([Formula: see text]-MST) problem is the problem of finding a spanning tree with maximum degree no more than [Formula: see text] for the set of points such the sum of the total length of its edges is minimum. Similarly, the Euclidean [Formula: see text]-minimum bottleneck spanning tree ([Formula: see text]-MBST) problem, is the problem of finding a degree-bounded spanning tree for a set of points in the plane such that the length of the longest edge is minimum. When [Formula: see text], these

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5

Wang, Hui, Xiucui Guan, Qiao Zhang, and Binwu Zhang. "Capacitated inverse optimal value problem on minimum spanning tree under bottleneck Hamming distance." Journal of Combinatorial Optimization 41, no. 4 (2021): 861–87. http://dx.doi.org/10.1007/s10878-021-00721-5.

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6

Rantala, Antti, Pauli Pihajoki, Matias Mannerkoski, Peter H. Johansson, and Thorsten Naab. "mstar – a fast parallelized algorithmically regularized integrator with minimum spanning tree coordinates." Monthly Notices of the Royal Astronomical Society 492, no. 3 (2020): 4131–48. http://dx.doi.org/10.1093/mnras/staa084.

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ABSTRACT We present the novel algorithmically regularized integration method mstar for high-accuracy (|ΔE/E| ≳ 10−14) integrations of N-body systems using minimum spanning tree coordinates. The twofold parallelization of the $\mathcal {O}(N_\mathrm{part}^2)$ force loops and the substep divisions of the extrapolation method allow for a parallel scaling up to NCPU = 0.2 × Npart. The efficient parallel scaling of mstar makes the accurate integration of much larger particle numbers possible compared to the traditional algorithmic regularization chain (ar-chain) methods, e.g. Npart = 5000 particles

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7

Hasuike, Takashi, Hideki Katagiri, and Hiroshi Tsuda. "Risk-Control Approach for a Bottleneck Spanning Tree Problem with the Total Network Reliability under Uncertainty." Journal of Applied Mathematics 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/364086.

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This paper considers a new risk-control and management approach for a bottleneck spanning tree problem under the situation where edge costs in a given network include randomness and reliability. Particularly, this paper focuses on the case that only mean value and variance of edge costs are calculated without assuming a specific random distribution. In order to develop the risk control approach, a confidence interval-based formulation is introduced. Using this interval, as well as minimizing the maximum value of worse edge costs, maximizing the minimum value of robust parameters to edge costs

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8

Wang, Ling Xiu, and Ye Wen Cao. "Ant Colony-Based Load Balancing Algorithm for Multi-Source Multicast Networks." Advanced Materials Research 204-210 (February 2011): 1399–402. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.1399.

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IP multicast protocols tend to construct a single minimum spanning tree for a multicast source (i.e., group), in which only a few internal nodes supply multicast traffic. In multicast networks especially with multiple multicast sources where bottleneck effects may occur frequently, frequently used multicast service leads to inefficient network utilization problems. This paper presents a new network utilization algorithm for multicasting called load distribution algorithm (LDA). The LDA algorithm uses selecting candidate path based on ant colony algorithm and multicast scheduling to distribute

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9

Zhang, Shun-Miao, Sheng-Bo Gao, Thi-Kien Dao, et al. "An Analysis Scheme of Balancing Energy Consumption with Mobile Velocity Control Strategy for Wireless Rechargeable Sensor Networks." Sensors 20, no. 16 (2020): 4494. http://dx.doi.org/10.3390/s20164494.

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Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and

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10

Bock, Clive H., Michael W. Hotchkiss, Carolyn A. Young, et al. "Population Genetic Structure of Venturia effusa, Cause of Pecan Scab, in the Southeastern United States." Phytopathology® 107, no. 5 (2017): 607–19. http://dx.doi.org/10.1094/phyto-10-16-0376-r.

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Venturia effusa is the most important pathogen of pecan in the southeastern United States. Little information exists on the population biology and genetic diversity of the pathogen. A hierarchical sampling of 784 isolates from 63 trees in 11 pecan orchards in the southeastern United States were screened against a set of 30 previously characterized microsatellite markers. Populations were collected from Georgia (n = 2), Florida (n = 1), Alabama (n = 2), Mississippi (n = 1), Louisiana (n = 1), Illinois (n = 1), Oklahoma (n = 1), Texas (n = 1), and Kansas (n = 1). Clonality was low in all orchard

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11

Ishii, Hiroaki, and Shōgo Shiode. "Chance constrained bottleneck spanning tree problem." Annals of Operations Research 56, no. 1 (1995): 177–87. http://dx.doi.org/10.1007/bf02031706.

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12

Vikas., C. S. "Minimum Spanning Tree Algorithm." International Journal of Computer Applications 1, no. 8 (2010): 39–45. http://dx.doi.org/10.5120/185-321.

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13

Chandrasekaran, V. T., and N. Rajasri. "Minimum Diameter Spanning Tree." American Journal of Computational Mathematics 08, no. 03 (2018): 203–8. http://dx.doi.org/10.4236/ajcm.2018.83016.

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14

Lee, Sang-Un. "Hybrid Minimum Spanning Tree Algorithm." KIPS Transactions:PartA 17A, no. 3 (2010): 159–66. http://dx.doi.org/10.3745/kipsta.2010.17a.3.159.

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15

Ciupala, Laura, Adrian Deaconu, and Delia Spridon. "Incremental minimum spanning tree algorithms." SERIES III - MATEMATICS, INFORMATICS, PHYSICS 13(62), no. 1 (2020): 343–46. http://dx.doi.org/10.31926/but.mif.2020.13.62.1.25.

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16

Sandoval, Leonidas. "Pruning a minimum spanning tree." Physica A: Statistical Mechanics and its Applications 391, no. 8 (2012): 2678–711. http://dx.doi.org/10.1016/j.physa.2011.12.052.

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17

Le, Phuoc Hoang, Tri-Dung Nguyen, and Tolga Bektaş. "Generalized minimum spanning tree games." EURO Journal on Computational Optimization 4, no. 2 (2015): 167–88. http://dx.doi.org/10.1007/s13675-015-0042-y.

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18

Jannah, Miftahul, Narwen Narwen, and Bukti Ginting. "MENCARI MINIMUM SPANNING TREE DENGAN KONSTREN." Jurnal Matematika UNAND 7, no. 4 (2019): 22. http://dx.doi.org/10.25077/jmu.7.4.22-26.2018.

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Misalkan G = (V, E) adalah graf tak berarah terhubung yang bukan tree, berarti di G terdapat cycle. Dengan cyclic interchange maka diperoleh subgraf T yang tidak memuat cycle. Subgraf T inilah yang dinamakan dengan spanning tree. Minimum spanning tree adalah spanning tree dengan jumlah bobot terkecil. Pada skripsi ini akan dibahas tentang bagaimana menentukan minimum spanning tree dengan konstren dari suatu graf terhubung sederhana.Kata Kunci: Spanning tree, Minimum spanning tree, Spanning tree dengan konstren

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19

Zhou, Jian, Xiajie Yi, Ke Wang, and Jing Liu. "Uncertain Distribution-Minimum Spanning Tree Problem." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 04 (2016): 537–60. http://dx.doi.org/10.1142/s0218488516500264.

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This paper studies the minimum spanning tree problem on a graph with uncertain edge weights, which are formulated as uncertain variables. The concept of ideal uncertain minimum spanning tree (ideal UMST) is initiated by extending the definition of the uncertain [Formula: see text]-minimum spanning tree to reect the overall properties of the α-minimum spanning tree weights at any confidence level [Formula: see text]. On the basis of this new concept, the definition of uncertain distribution-minimum spanning tree is proposed in three ways. Particularly, by considering the tail value at risk from

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20

Zakiah, Nina. "DIAGRAM ALIR ALGORITMA KRUSKAL DALAM MENENTUKAN MINIMUM SPANNING TREE." JURNAL MATHEMATIC PAEDAGOGIC 5, no. 2 (2021): 151–57. http://dx.doi.org/10.36294/jmp.v5i2.1977.

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AbstractThe flow chart of the minimum spanning tree is represented in a weight matrix as a form of development of the link matrix. Determining the minimum spanning tree in this journal uses the Kruskal algorithm and is implemented in the form of a flow chart. This journal is a study of theories regarding the minimum spanning tree determination problem. With the problem approach, namely: graph theory, trees, determination of Minimum spanning tree, Kruskal's algorithm and flow diagrams. Furthermore, it is implemented in the flowchart of determining the Minimum spanning tree. Keywords: Minimum sp

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21

V. T. Chandrasekaran, and N. Rajasri. "Domination on Minimum Diameter Spanning Tree." International Journal of Research in Advent Technology 7, no. 1 (2019): 164–68. http://dx.doi.org/10.32622/ijrat.71201949.

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22

Choi, Myeong-Bok, and Sang-Un Lee. "Generalized Borůvka's Minimum Spanning Tree Algorithm." Journal of the Institute of Webcasting, Internet and Telecommunication 12, no. 6 (2012): 165–73. http://dx.doi.org/10.7236/jiwit.2012.12.6.165.

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23

Biswal, Sagarika, and S. P. Mohanty. "Minimum Spanning Tree with Rough Weights." International Journal of Computer Applications 71, no. 12 (2013): 27–32. http://dx.doi.org/10.5120/12412-9154.

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24

Chen, Guangting, and Guochuan Zhang. "A constrained minimum spanning tree problem." Computers & Operations Research 27, no. 9 (2000): 867–75. http://dx.doi.org/10.1016/s0305-0548(99)00061-1.

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25

Pettie, Seth, and Vijaya Ramachandran. "An optimal minimum spanning tree algorithm." Journal of the ACM 49, no. 1 (2002): 16–34. http://dx.doi.org/10.1145/505241.505243.

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26

Hassin, Refael, and Asaf Levin. "Minimum spanning tree with hop restrictions." Journal of Algorithms 48, no. 1 (2003): 220–38. http://dx.doi.org/10.1016/s0196-6774(03)00051-8.

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27

Peter, S. John. "Outlier removal through minimum spanning tree." Journal of Discrete Mathematical Sciences and Cryptography 15, no. 2-3 (2012): 159–70. http://dx.doi.org/10.1080/09720529.2012.10698372.

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28

Assad, Arjang, and Weixuan Xu. "The quadratic minimum spanning tree problem." Naval Research Logistics 39, no. 3 (1992): 399–417. http://dx.doi.org/10.1002/1520-6750(199204)39:3<399::aid-nav3220390309>3.0.co;2-0.

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29

Paschos, Stratos A., and Vangelis Th Paschos. "Reoptimization of the minimum spanning tree." Wiley Interdisciplinary Reviews: Computational Statistics 4, no. 2 (2011): 211–17. http://dx.doi.org/10.1002/wics.204.

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30

Bertsimas, Dimitris J. "The probabilistic minimum spanning tree problem." Networks 20, no. 3 (1990): 245–75. http://dx.doi.org/10.1002/net.3230200302.

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31

Dewi, M. P., A. Armiati, and S. Alvini. "Image Segmentation Using Minimum Spanning Tree." IOP Conference Series: Materials Science and Engineering 335 (April 2018): 012135. http://dx.doi.org/10.1088/1757-899x/335/1/012135.

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32

Jin, Yusheng, Hong Zhao, Feifei Gu, Penghui Bu, and Mulun Na. "A spatial minimum spanning tree filter." Measurement Science and Technology 32, no. 1 (2020): 015204. http://dx.doi.org/10.1088/1361-6501/abaa65.

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33

Bianchi, Maria Paola, Hans-Joachim Böckenhauer, Tatjana Brülisauer, Dennis Komm, and Beatrice Palano. "Online Minimum Spanning Tree with Advice." International Journal of Foundations of Computer Science 29, no. 04 (2018): 505–27. http://dx.doi.org/10.1142/s0129054118410034.

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In the online minimum spanning tree problem, a graph is revealed vertex by vertex; together with every vertex, all edges to vertices that are already known are given, and an online algorithm must irrevocably choose a subset of them as a part of its solution. The advice complexity of an online problem is a means to quantify the information that needs to be extracted from the input to achieve good results. For a graph of size [Formula: see text], we show an asymptotically tight bound of [Formula: see text] on the number of advice bits to produce an optimal solution for any given graph. For parti

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34

Gao, Jinwu, and Mei Lu. "Fuzzy quadratic minimum spanning tree problem." Applied Mathematics and Computation 164, no. 3 (2005): 773–88. http://dx.doi.org/10.1016/j.amc.2004.06.051.

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35

Carmi, Paz, Matthew J. Katz, and Joseph S. B. Mitchell. "The minimum-area spanning tree problem." Computational Geometry 35, no. 3 (2006): 218–25. http://dx.doi.org/10.1016/j.comgeo.2006.03.001.

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36

Cardinal, Jean, Erik D. Demaine, Samuel Fiorini, et al. "The Stackelberg Minimum Spanning Tree Game." Algorithmica 59, no. 2 (2009): 129–44. http://dx.doi.org/10.1007/s00453-009-9299-y.

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37

Dubinsky, Manuel, César Massri, and Gabriel Taubin. "Minimum Spanning Tree Cycle Intersection problem." Discrete Applied Mathematics 294 (May 2021): 152–66. http://dx.doi.org/10.1016/j.dam.2021.01.031.

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38

Thasya, Laksmi Charina, and Narwen . "MENENTUKAN MINIMUM SPANNING TREE DENGAN MENGGUNAKAN DETERMINAN." Jurnal Matematika UNAND 7, no. 2 (2018): 84. http://dx.doi.org/10.25077/jmu.7.2.84-88.2018.

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Abstrak. Terdapat beberapa metoda untuk mencari sebuah minimum spanning treedalam graf terhubung dengan pembobotan. Diantaranya dengan menggunakan determi-nan submatriks non singular dari matriks insidensi graf yang diberikan. Pada tulisan iniakan dibahas tentang bagaimana menentukan minimum spanning tree dengan menggu-nakan determinan.Kata Kunci: Spanning tree, Minimum spanning tree, Determinan dari matriks insidensibobot sisi

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39

ZHOU, YAN, OLEKSANDR GRYGORASH, and THOMAS F. HAIN. "CLUSTERING WITH MINIMUM SPANNING TREES." International Journal on Artificial Intelligence Tools 20, no. 01 (2011): 139–77. http://dx.doi.org/10.1142/s0218213011000061.

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We propose two Euclidean minimum spanning tree based clustering algorithms — one a k-constrained, and the other an unconstrained algorithm. Our k-constrained clustering algorithm produces a k-partition of a set of points for any given k. The algorithm constructs a minimum spanning tree of a set of representative points and removes edges that satisfy a predefined criterion. The process is repeated until k clusters are produced. Our unconstrained clustering algorithm partitions a point set into a group of clusters by maximally reducing the overall standard deviation of the edges in the Euclidean

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40

TUMMINELLO, MICHELE, CLAUDIA CORONNELLO, FABRIZIO LILLO, SALVATORE MICCICHÈ, and ROSARIO N. MANTEGNA. "SPANNING TREES AND BOOTSTRAP RELIABILITY ESTIMATION IN CORRELATION-BASED NETWORKS." International Journal of Bifurcation and Chaos 17, no. 07 (2007): 2319–29. http://dx.doi.org/10.1142/s0218127407018415.

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We introduce a new technique to associate a spanning tree to the average linkage cluster analysis. We term this tree as the Average Linkage Minimum Spanning Tree. We also introduce a technique to associate a value of reliability to the links of correlation-based graphs by using bootstrap replicas of data. Both techniques are applied to the portfolio of the 300 most capitalized stocks traded on the New York Stock Exchange during the time period 2001–2003. We show that the Average Linkage Minimum Spanning Tree recognizes economic sectors and sub-sectors as communities in the network slightly bet

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41

Di Giacomo, Emilio, Walter Didimo, Giuseppe Liotta, and Henk Meijer. "Drawing a tree as a minimum spanning tree approximation." Journal of Computer and System Sciences 78, no. 2 (2012): 491–503. http://dx.doi.org/10.1016/j.jcss.2011.06.001.

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42

Dili, Yusufiani Nurlinawati. "PENYELESAIAN MASALAH TRANSPORTASI UNTUK MENCARI SOLUSI OPTIMAL DENGAN PENDEKATAN MINIMUM SPANNING TREE (MST) MENGGUNAKAN ALGORITMA KRUSKAL DAN ALGORITMA PRIM." KUBIK: Jurnal Publikasi Ilmiah Matematika 6, no. 1 (2021): 44–50. http://dx.doi.org/10.15575/kubik.v6i1.13907.

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Penelitian ini membahas tentang penyelesaian masalah transportasi dengan pendekatan Minimum Spanning Tree (MST) menggunakan algoritma Kruskal dan algoritma Prim untuk mencari solusi optimal. Algoritma Kruskal dan algoritma Prim merupakan algoritma dalam teori graf untuk mencari Minimum Spanning Tree (MST). Langkah algoritma Kruskal yaitu mengurutkan biaya dari yang terkecil hingga terbesar. Selanjutnya, pilih biaya yang paling terkecil. Kemudian, lakukan perhitungan dengan melihat sumber persediaan dan permintaan di setiap tujuan sampai semuanya terpenuhi, sehingga terlihat bentuk Minimum Span

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43

Punnen, Abraham P., and K. P. K. Nair. "An Improved Algorithm for the Constrained Bottleneck Spanning Tree Problem." INFORMS Journal on Computing 8, no. 1 (1996): 41–44. http://dx.doi.org/10.1287/ijoc.8.1.41.

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44

Ahmadi, Hamed, and José R. Martí. "Minimum-loss network reconfiguration: A minimum spanning tree problem." Sustainable Energy, Grids and Networks 1 (March 2015): 1–9. http://dx.doi.org/10.1016/j.segan.2014.10.001.

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45

Sun, Xuemei, Cheng Chang, Hua Su, and Chuitian Rong. "Novel Degree Constrained Minimum Spanning Tree Algorithm Based on an Improved Multicolony Ant Algorithm." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/601782.

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Degree constrained minimum spanning tree (DCMST) refers to constructing a spanning tree of minimum weight in a complete graph with weights on edges while the degree of each node in the spanning tree is no more thand(d≥ 2). The paper proposes an improved multicolony ant algorithm for degree constrained minimum spanning tree searching which enables independent search for optimal solutions among various colonies and achieving information exchanges between different colonies by information entropy. Local optimal algorithm is introduced to improve constructed spanning tree. Meanwhile, algorithm str

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46

FUJIYOSHI, Akio, and Masakazu SUZUKI. "Minimum Spanning Tree Problem with Label Selection." IEICE Transactions on Information and Systems E94-D, no. 2 (2011): 233–39. http://dx.doi.org/10.1587/transinf.e94.d.233.

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47

Chen, Bang Ze, and Xiao Bo Yang. "Minimum Spanning Tree Dynamic Demonstration System Implementation." Applied Mechanics and Materials 397-400 (September 2013): 2526–30. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2526.

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The graph vertices design into classes, for each vertex in the design of the abscissa, ordinate and in-degree members, realizes the dynamic demonstration minimum spanning tree. Dynamic visualize Prime algorithm and kruskal algorithm implementation process. Around two window synchronization of animation, " in order to find the minimum edge " list box list the minimum edge of a minimum spanning tree ,with thick line in the left window drawing the found minimum edge and On the edge of the vertex, in the right box demo the process of algorithm dynamic execution.

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48

Banu, Farhan. "Matrix Method for Determining Minimum Spanning Tree." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 8, no. 3 (2020): 29–33. http://dx.doi.org/10.37082/ijirmps.2020.v08i03.005.

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49

Akbari Torkestani, Javad. "Stochastic Bounded Diameter Minimum Spanning Tree Problem." Fundamenta Informaticae 140, no. 2 (2015): 205–19. http://dx.doi.org/10.3233/fi-2015-1250.

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50

Hage, Per, Frank Harary, and Brent James. "The Minimum Spanning Tree Problem in Archaeology." American Antiquity 61, no. 1 (1996): 149–55. http://dx.doi.org/10.2307/282309.

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The minimum spanning tree problem is a well-known problem of combinatorial optimization. It was independently discovered in archaeology by Renfrew and Sterud in their method of close proximity analysis. Unlike traditional methods of seriation, this method permits branching structures that reveal clustering in archaeological data. Identifying close proximity analysis as the minimum spanning tree problem permits a more efficient means of computation, an explicit rule of clustering, and a recognition of problems of indeterminacy in the analysis of network data. These points are illustrated with r

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