New heuristic algorithm for unweighted minimum vertex cover

Uğurlu, Onur

doi:10.1109/icpci.2012.6486444

Cited by 8 publications

(4 citation statements)

References 6 publications

(5 reference statements)

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“…In this section, we investigate studies related to vertex cover and its varieties. In [26], isolation algorithm that is a heuristic method aiming to solve minimum VC problem has been proposed. Measurements taken on widely used datasets revealed that the proposed algorithm performs well when the graph size is small.…”

Section: Related Workmentioning

confidence: 99%

Weighted Connected Vertex Cover Based Energy-Efficient Link Monitoring for Wireless Sensor Networks Towards Secure Internet of Things

Dagdeviren

2021

IEEE Access

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Industry 4.0 utilizes the Internet of Things (IoT) to rise the efficiency in manufacturing and automation where wireless sensor networks (WSNs) are crucial technologies for communication layer of IoT. WSNs include hundreds of small sized sensor nodes that have the abilities of wireless transmission and environmental sensing. Wireless transmission is prone to various attacks such as data manipulation since data communication is achieved through transfer of radio packets. A countermeasure of this issue is link monitoring by deploying secure points that can physically capture and inspect radio packets. Graph theory plays a critical role to solve various problems in WSNs. Finding minimum Vertex Cover (VC) is an important NP-Hard graph theoretic problem in which the minimum set of nodes (vertices) is aimed to select in such a way that each link should be incident to at least one node from this set. VC is a significant structure for WSNs where it perfectly fits for link monitoring when nodes in VC are set as secure points (monitors). Since sensor nodes are generally battery-powered and have limited transmission range, energy-efficient multi-hop communication to the sink node is of utmost importance. In weighted connected VC (WCVC) structure, subgraph induced by monitor nodes are connected where monitors are chosen according to their weights. When weights of nodes are assigned as reciprocal of their energies, an energy-efficient virtual backbone can be formed. We propose a novel metaheuristic WCVC algorithm for link monitoring and backbone formation in WSNs modeled as undirected graphs. Our proposed algorithm integrates a genetic search with a greedy heuristic to improve WCVC solution quality and decrease the search time. To evaluate the efficiencies of greedy heuristics, we adopt three different heuristics for WCVC problem. We implement our algorithm with its counterparts and reveal that the algorithm is favorable in terms of solution quality and resource consumption. INDEX TERMS Internet of things, wireless sensor networks, link monitoring, vertex cover, metaheuristic algorithm.

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Section: Related Workmentioning

confidence: 99%

Weighted Connected Vertex Cover Based Energy-Efficient Link Monitoring for Wireless Sensor Networks Towards Secure Internet of Things

Dagdeviren

2021

IEEE Access

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“…In spite of this growing attention, there does not currently exist a method for computing src(G) in general graphs G. Previous work on variants of the rainbow connection problem have proposed heuristic methods to produce rainbow colorings [5,10,36]. However, even in the event that these methods find an optimal solution, they are unable to provide certificates of optimality.…”

Section: Background and Motivationmentioning

confidence: 99%

“…To the best knowledge of the authors, no heuristic method has been proposed for strong rainbow connection in general graphs. Polynomial heuristic methods have been proposed for several related problems however, including the rainbow vertex connection problem [36] and the rainbow connection problem, both in general graphs [5] and in the special case of maximal outer planer graphs [10]. Since the upper bounds provided by heuristic methods can often be used to significantly assist with the computational methods, it is desirable to also have a heuristic method for strong rainbow connection.…”

Section: A Fast Random Heuristic For (Strong) Rainbow Connectionmentioning

confidence: 99%

An integer program and new lower bounds for computing the strong rainbow connection numbers of graphs

Smith¹,

Mildebrath²,

Hicks³

2020

Preprint

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We present an integer programming model to compute the strong rainbow connection number src(G) of any simple graph G. We introduce several enhancements to the proposed model, including a fast heuristic, a novel class of valid inequalities, and a variable elimination scheme. Moreover, we present a novel lower bound for src(G) which may be of independent research interest. We evaluate our model with a traditional branch and cut approach as well as an alternative scheme based on iterative lower bound improvement, which we show to be highly effective in practice. To our knowledge, these are the first computational methods for the strong rainbow connection problem. We demonstrate the efficacy of our methods by computing the strong rainbow connection numbers of graphs with up to 167 vertices.

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“…As the size of the problem increases, these methods become futile. Meta-heuristics are powerful search methods which can be efficiently in providing satisfactory solutions to large and complex problems such as vertex cover [20], dominating set [14] and edge coloring [16] in a reasonable time. However, up to the authors' knowledge, there are no studies up to day used meta-heuristic techniques for solving the MWEDS problem.…”

Section: Introductionmentioning

confidence: 99%

Memetic Algorithm with Filtering Scheme for the Minimum Weighted Edge Dominating Set Problem

Abdulaziz¹,

Hedar²,

Sewisy³

2013

IJARAI

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Abstract-The minimum weighted edge dominating set problem (MWEDS) generalizes both the weighted vertex cover problem and the problem of covering the edges of graph by a minimum cost set of both vertices and edges. In this paper, we propose a meta-heuristic approach based on genetic algorithm and local search to solve the MWEDS problem. Therefore, the proposed method is considered as a memetic search algorithm which is called Memetic Algorithm with filtering scheme for minimum weighted edge dominating set, and called shortly (MAFS). In the MAFS method, three new fitness functions are invoked to effectively measure the solution qualities. The search process in the proposed method uses intensification scheme, called "filtering", beside the main genetic search operations in order to achieve faster performance. The experimental results proves that the proposed method is promising in solving the MWEDS problem.

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New heuristic algorithm for unweighted minimum vertex cover

Cited by 8 publications

References 6 publications

Weighted Connected Vertex Cover Based Energy-Efficient Link Monitoring for Wireless Sensor Networks Towards Secure Internet of Things

Weighted Connected Vertex Cover Based Energy-Efficient Link Monitoring for Wireless Sensor Networks Towards Secure Internet of Things

An integer program and new lower bounds for computing the strong rainbow connection numbers of graphs

Memetic Algorithm with Filtering Scheme for the Minimum Weighted Edge Dominating Set Problem

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