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A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem

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  • Saad Alharbi
  • Ibrahim Venkat

Abstract

In the field of computing, combinatorics, and related areas, researchers have formulated several techniques for the Minimum Dominating Set of Queens Problem (MDSQP) pertaining to the typical chessboard based puzzles. However, literature shows that limited research has been carried out to solve the MDSQP using bioinspired algorithms. To fill this gap, this paper proposes a simple and effective solution based on genetic algorithms to solve this classical problem. We report results which demonstrate that near optimal solutions have been determined by the GA for different board sizes ranging from 8 × 8 to 11 × 11.

Suggested Citation

  • Saad Alharbi & Ibrahim Venkat, 2017. "A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem," Journal of Optimization, Hindawi, vol. 2017, pages 1-8, June.
    • Handle: RePEc:hin:jjopti:5650364
    DOI: 10.1155/2017/5650364
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    References listed on IDEAS

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    1. Marinakis, Yannis & Migdalas, Athanasios & Sifaleras, Angelo, 2017. "A hybrid Particle Swarm Optimization – Variable Neighborhood Search algorithm for Constrained Shortest Path problems," European Journal of Operational Research, Elsevier, vol. 261(3), pages 819-834.
    2. Ellips Masehian & Hossein Akbaripour & Nasrin Mohabbati-Kalejahi, 2013. "Landscape analysis and efficient metaheuristics for solving the n-queens problem," Computational Optimization and Applications, Springer, vol. 56(3), pages 735-764, December.
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    Cited by:

    1. Nuño, Juan Carlos & Muñoz, Francisco J., 2020. "The partial visibility curve of the Feigenbaum cascade to chaos," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).

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