A Smart Approximation Algorithm for Minimum Vertex Cover Problem based on Min-to-Min (MtM) Strategy

Haider, Jawad; Fayaz, Muhammad

doi:10.14569/ijacsa.2020.0111232

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…However, when all edges are covered by a minimum number of nodes, it is referred to as MVCP. MVCP is an NP-Complete optimization problem that is difficult to solve in polynomial time (Haider & Fayaz, 2020). Many algorithms have been proposed and approaches have been developed to solve this problem.…”

Section: Introductionmentioning

confidence: 99%

A New Approach Based on Centrality Value in Solving the Minimum Vertex Cover Problem: Malatya Centrality Algorithm

Karcı

Yakut

Öztemiz

2022

AB-BBD

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The graph is a data structures and models that used to describe many real-world problems. Many engineering problems, such as safety and transportation, have a graph-like structure and are based on a similar model. Therefore, these problems can be solved using similar methods to the graph data model. Vertex cover problem that is used in modeling many problems is one of the important NP-complete problems in graph theory. Vertex-cover realization by using minimum number of vertex is called Minimum Vertex Cover Problem (MVCP). Since MVCP is an optimization problem, many algorithms and approaches have been proposed to solve this problem. In this article, Malatya algorithm, which offers an effective solution for the vertex-cover problem, is proposed. Malatya algorithm offers a polynomial approach to the vertex cover problem. In the proposed approach, MVCP consists of two steps, calculating the Malatya centrality value and selecting the covering nodes. In the first step, Malatya centrality values are calculated for the nodes in the graph. These values are calculated using Malatya algorithm. Malatya centrality value of each node in the graph consists of the sum of the ratios of the degree of the node to the degrees of the adjacent nodes. The second step is a node selection problem for the vertex cover. The node with the maximum Malatya centrality value is selected from the nodes in the graph and added to the solution set. Then this node and its coincident edges are removed from the graph. Malatya centrality values are calculated again for the new graph, and the node with the maximum Malatya centrality value is selected from these values, and the coincident edges to this node are removed from the graph. This process is continued until all the edges in the graph are covered. It is shown on the sample graph that the proposed Malatya algorithm provides an effective solution for MVCP. Successful test results and analyzes show the effectiveness of Malatya algorithm.

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Section: Introductionmentioning

confidence: 99%