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A heterogeneous cellular processing algorithm for minimizing the power consumption in wireless communications systems

Author

Listed:
  • J. Terán-Villanueva
  • Héctor Fraire Huacuja
  • Juan Carpio Valadez
  • Rodolfo Pazos Rangel
  • Héctor Puga Soberanes
  • José Martínez Flores

Abstract

In this paper, the NP-hard problem of minimizing power consumption in wireless communications systems is approached. In the literature, several metaheuristic approaches have been proposed to solve it. Currently a homogeneous cellular processing algorithm and a GRASP algorithm hybridized with path-relinking are considered the state of the art algorithms. The main contribution of this paper is the analysis of five main characteristics for a heterogeneous cellular processing algorithm, based on scatter search and GRASP. A series of computational experiments with standard instances were carried out to assess the impact of each one of these characteristics. Among the main analyses we found particularly interesting a time reduction by 74.24 %, produced by the stagnation detection characteristic. Also the communication characteristic improves the quality of the solutions by 24.73 %. The computational results show that our heterogeneous cellular processing algorithm is a good alternative for solving the problem. The proposed algorithm finds 34 new best known solutions, which is 27 % of the instances with unknown optimal values. A Friedman hypothesis test was carried out to validate that two state-of-the-art algorithms and the proposed algorithm are statistically equivalent. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • J. Terán-Villanueva & Héctor Fraire Huacuja & Juan Carpio Valadez & Rodolfo Pazos Rangel & Héctor Puga Soberanes & José Martínez Flores, 2015. "A heterogeneous cellular processing algorithm for minimizing the power consumption in wireless communications systems," Computational Optimization and Applications, Springer, vol. 62(3), pages 787-814, December.
    • Handle: RePEc:spr:coopap:v:62:y:2015:i:3:p:787-814
    DOI: 10.1007/s10589-015-9754-4
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    References listed on IDEAS

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    1. Duarte, Abraham & Martí, Rafael & Álvarez, Ada & Ángel-Bello, Francisco, 2012. "Metaheuristics for the linear ordering problem with cumulative costs," European Journal of Operational Research, Elsevier, vol. 216(2), pages 270-277.
    2. Mauricio G.C. Resende & Celso C. Ribeiro & Fred Glover & Rafael Martí, 2010. "Scatter Search and Path-Relinking: Fundamentals, Advances, and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 87-107, Springer.
    3. Righini, Giovanni, 2008. "A branch-and-bound algorithm for the linear ordering problem with cumulative costs," European Journal of Operational Research, Elsevier, vol. 186(3), pages 965-971, May.
    4. Abraham Duarte & Manuel Laguna & Rafael Martí, 2011. "Tabu search for the linear ordering problem with cumulative costs," Computational Optimization and Applications, Springer, vol. 48(3), pages 697-715, April.
    5. Thomas A. Feo & Mauricio G. C. Resende & Stuart H. Smith, 1994. "A Greedy Randomized Adaptive Search Procedure for Maximum Independent Set," Operations Research, INFORMS, vol. 42(5), pages 860-878, October.
    6. Dario Landa-Silva & Edmund K. Burke, 2007. "Asynchronous Cooperative Local Search for the Office-Space-Allocation Problem," INFORMS Journal on Computing, INFORMS, vol. 19(4), pages 575-587, November.
    7. Bertacco, Livio & Brunetta, Lorenzo & Fischetti, Matteo, 2008. "The Linear Ordering Problem with cumulative costs," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1345-1357, September.
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