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Evaluation performance of genetic algorithm and tabu search algorithm for solving the Max-RWA problem in all-optical networks

Author

Listed:
  • Fouad Kharroubi

    (Hunan University)

  • Jing He

    (Hunan University)

  • Jin Tang

    (Hunan University)

  • Ming Chen

    (Hunan University)

  • Lin Chen

    (Hunan University)

Abstract

In this paper, we deal with the static Routing and Wavelength Assignment (RWA) problem in networks with no wavelength converters, and where a given static set of connection demands is prearranged. Our objective is to maximize the number of optical connection-requests that can be established for a given number of wavelengths. A mathematical formulation for Max-RWA was presented. In this article, we implement and compare the performance of two random search algorithms namely: the genetic algorithm and the tabu search algorithm. Using these metaheuristics we solved approximately the wavelength assignment problem for Max-RWA while we computed its routing by a deterministic method which is the backtracking. Therefore we conducted many extensive experiments under different circumstances. Diagrams and representative numerical examples indicate the accuracy of our algorithms.

Suggested Citation

  • Fouad Kharroubi & Jing He & Jin Tang & Ming Chen & Lin Chen, 2015. "Evaluation performance of genetic algorithm and tabu search algorithm for solving the Max-RWA problem in all-optical networks," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 1042-1061, November.
    • Handle: RePEc:spr:jcomop:v:30:y:2015:i:4:d:10.1007_s10878-013-9676-y
    DOI: 10.1007/s10878-013-9676-y
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    References listed on IDEAS

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    1. Carlos A.S. Oliveira & Panos M. Pardalos, 2011. "Mathematical Aspects of Network Routing Optimization," Springer Optimization and Its Applications, Springer, number 978-1-4614-0311-1, June.
    2. Thiago Noronha & Mauricio Resende & Celso Ribeiro, 2011. "A biased random-key genetic algorithm for routing and wavelength assignment," Journal of Global Optimization, Springer, vol. 50(3), pages 503-518, July.
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    Cited by:

    1. Jaromír Kukal & Matej Mojzeš, 2018. "Quantile and mean value measures of search process complexity," Journal of Combinatorial Optimization, Springer, vol. 35(4), pages 1261-1285, May.

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