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DOI: 10.14569/IJARAI.2013.020808
PDF

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

Author 1: Abdel Rahman Hedar
Author 2: Shada N. Abdel-Aziz
Author 3: Adel A. Sewisy

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 8, 2013.

  • Abstract and Keywords
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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

Keywords: Minimum weight edge dominating set, Graph theory, Genetic algorithm, Memetic algorithm, Local search.

Abdel Rahman Hedar, Shada N. Abdel-Aziz and Adel A. Sewisy, “Memetic Algorithm with Filtering Scheme for the Minimum Weighted Edge Dominating Set Problem” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(8), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020808

@article{Hedar2013,
title = {Memetic Algorithm with Filtering Scheme for the Minimum Weighted Edge Dominating Set Problem},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.020808},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020808},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {8},
author = {Abdel Rahman Hedar and Shada N. Abdel-Aziz and Adel A. Sewisy}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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