Counting Weighted Spanning Trees to Solve Constrained Minimum Spanning Tree Problems

Author(s):  
Antoine Delaite ◽  
Gilles Pesant
2016 ◽  
Vol 62 (4) ◽  
pp. 379-388 ◽  
Author(s):  
Iwona Dolińska ◽  
Mariusz Jakubowski ◽  
Antoni Masiukiewicz ◽  
Grzegorz Rządkowski ◽  
Kamil Piórczyński

Abstract Channel assignment in 2.4 GHz band of 802.11 standard is still important issue as a lot of 2.4 GHz devices are in use. This band offers only three non-overlapping channels, so in crowded environment users can suffer from high interference level. In this paper, a greedy algorithm inspired by the Prim’s algorithm for finding minimum spanning trees (MSTs) in undirected graphs is considered for channel assignment in this type of networks. The proposed solution tested for example network distributions achieves results close to the exhaustive approach and is, in many cases, several orders of magnitude faster.


2019 ◽  
Vol 1 (1) ◽  
pp. 27
Author(s):  
Devi Lastri ◽  
Masriani ◽  
Nadia W ◽  
Parizal Hidayatullah ◽  
Wahyu Ulfayandhie Misuki ◽  
...  

The kruskal algorithm is an algorithm to search for minimum spanning trees directly based on the general MST (Minimum Spanning Tree) algorithm. In the kruskal algorithm, the sides in the graph are sorted first based on their weight from small to large. The kruskal algorithm in the search for a minimum spanning tree can be applied to the distribution of clean water of PDAM in North Lombok district. This problem is intended to get the shortest route for PDAM water distribution in North Lombok district in order to minimize costs.


Author(s):  
S. Dutta ◽  
D. Patra ◽  
H. Shankar ◽  
P. Alok Verma

minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim’s algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it’s minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several cities optimally or connecting all cities with minimum total road length.


2019 ◽  
Vol 91 (2) ◽  
pp. 61-80 ◽  
Author(s):  
Przemysław Śleszyński ◽  
Paweł Sudra

Contemporary settlement systems observed in Poland bear numerous traces of historical transformations of rural settlements which took place in the 19th century, at the time of foreign partitioning of Polish territory, in different ways in particular regions. The result of processes occurring from the second half of the 20th century is the extensive development of urban areas, and – after 1990 – chaotic, spontaneous processes of transformation in suburban zones. Research methods using graph theory have been applied for years in investigating settlement networks on various scales. One of the more useful graphs is the minimum spanning tree (MST), which connects all vertices in such a way that the sum of the distances between them is the shortest. This article presents the application of the minimum spanning tree (or shortest dendrite) method with a view to its suitability for determining the degree of dispersion and spatial cohesion of urbanised structures being assessed. Two indicators have been proposed thanks to alignment of the shortest dendrite length to other variables. The settlement network effectiveness indicator is the ratio of MST length to the population in an area. The settlement network cohesion indicator is in turn the ratio of the MST length to population density. Mazowieckie voivodeship has been chosen as the research area, while address points obtained from the central official database collecting data from municipal records have been chosen as the source dataset. Over 1 million address points were considered, in line with their status as at the end of 2016. Minimum spanning trees were plotted for each of the 314 gminas (local-authority areas) aking up the voivodeship, using ArcGIS software. Subsequently, the proposed indicators were calculated by reference to the MSTs. The results were then mapped. The proposed indicators may be helpful in studies on the origin of settlements, allowing areas with varying degrees of uniformity or isolation of building locations to be indicated. They can be made use of in comparative studies, especially concerning rural settlements, in which single-family housing predominates, and hamlets and uildings standing in isolation are present. The effectiveness indicator can be used in the assessment of infrastructural coverage, i.a. in the ontext of the costs of spatial chaos and demographic capacity.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Saeedeh Pourahmad ◽  
Atefeh Basirat ◽  
Amir Rahimi ◽  
Marziyeh Doostfatemeh

Random selection of initial centroids (centers) for clusters is a fundamental defect in K-means clustering algorithm as the algorithm’s performance depends on initial centroids and may end up in local optimizations. Various hybrid methods have been introduced to resolve this defect in K-means clustering algorithm. As regards, there are no comparative studies comparing these methods in various aspects, the present paper compared three hybrid methods with K-means clustering algorithm using concepts of genetic algorithm, minimum spanning tree, and hierarchical clustering method. Although these three hybrid methods have received more attention in previous researches, fewer studies have compared their results. Hence, seven quantitative datasets with different characteristics in terms of sample size, number of features, and number of different classes are utilized in present study. Eleven indices of external and internal evaluating index were also considered for comparing the methods. Data indicated that the hybrid methods resulted in higher convergence rate in obtaining the final solution than the ordinary K-means method. Furthermore, the hybrid method with hierarchical clustering algorithm converges to the optimal solution with less iteration than the other two hybrid methods. However, hybrid methods with minimal spanning trees and genetic algorithms may not always or often be more effective than the ordinary K-means method. Therefore, despite the computational complexity, these three hybrid methods have not led to much improvement in the K-means method. However, a simulation study is required to compare the methods and complete the conclusion.


Author(s):  
Wen-Chih Chang ◽  
Te-Hua Wang ◽  
Yan-Da Chiu

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


2011 ◽  
Vol 20 (01) ◽  
pp. 139-177 ◽  
Author(s):  
YAN ZHOU ◽  
OLEKSANDR GRYGORASH ◽  
THOMAS F. HAIN

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 minimum spanning tree constructed from a given point set, without prescribing the number of clusters. We present our experimental results comparing our proposed algorithms with k-means, X-means, CURE, Chameleon, and the Expectation-Maximization (EM) algorithm on both artificial data and benchmark data from the UCI repository. We also apply our algorithms to image color clustering and compare them with the standard minimum spanning tree clustering algorithm as well as CURE, Chameleon, and X-means.


2010 ◽  
Vol 21 (04) ◽  
pp. 471-480 ◽  
Author(s):  
XIAOBING FENG ◽  
XIAOFAN WANG

Although recently there are extensive research on currency network using minimum spanning trees approach, the knowledge about the actual evolution of a currency web in Asia is still limited. In the paper, we study the structural evolution of an Asian network using daily exchange rate data. It was found that the correlation between Asian currencies and US Dollar, the previous regional key currency has become weaker and the intra-Asia interactions have increased. This becomes more salient after the exchange rate reform of China. Different from the previous studies, we further reveal that it is the trade volume, national wealth gap and countries growth cycle that has contributed to the evolutionary topology of the minimum spanning tree. These findings provide a valuable platform for theoretical modeling and further analysis.


10.37236/1519 ◽  
2000 ◽  
Vol 7 (1) ◽  
Author(s):  
Alan Frieze ◽  
Miklós Ruszinkó ◽  
Lubos Thoma

Consider a connected $r$-regular $n$-vertex graph $G$ with random independent edge lengths, each uniformly distributed on $[0,1]$. Let $mst(G)$ be the expected length of a minimum spanning tree. We show in this paper that if $G$ is sufficiently highly edge connected then the expected length of a minimum spanning tree is $\sim {n\over r}\zeta(3)$. If we omit the edge connectivity condition, then it is at most $\sim {n\over r}(\zeta(3)+1)$.


2007 ◽  
Vol 17 (07) ◽  
pp. 2319-2329 ◽  
Author(s):  
MICHELE TUMMINELLO ◽  
CLAUDIA CORONNELLO ◽  
FABRIZIO LILLO ◽  
SALVATORE MICCICHÈ ◽  
ROSARIO N. MANTEGNA

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 better than the Minimum Spanning Tree. We also show that the average reliability of links in the Minimum Spanning Tree is slightly greater than the average reliability of links in the Average Linkage Minimum Spanning Tree.


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