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    Hybridization of Evolutionary Operators with Elitist Iterated Racing for the Simulation Optimization of Traffic Lights Programs.

    • Autor
      Cintrano López, Christian; Ferrer-Urbano, Francisco JavierAutoridad Universidad de Málaga; López-Ibáñez, Manuel; Alba-Torres, EnriqueAutoridad Universidad de Málaga
    • Fecha
      2023-03
    • Editorial/Editor
      MIT Press Direct
    • Palabras clave
      Tráfico - Regulación - Métodos de simulación
    • Resumen
      In the traffic light scheduling problem, the evaluation of candidate solutions requires the simulation of a process under various (traffic) scenarios. Thus, good solutions should not only achieve good objective function values, but they must be robust (low variance) across all different scenarios. Previous work has shown that combining IRACE with evolutionary operators is effective for this task due to the power of evolutionary operators in numerical optimization. In this article, we further explore the hybridization of evolutionary operators and the elitist iterated racing of IRACE for the simulation–optimization of traffic light programs. We review previous works from the literature to find the evolutionary operators performing the best when facing this problem to propose new hybrid algorithms. We evaluate our approach over a realistic case study derived from the traffic network of Málaga (Spain) with 275 traffic lights that should be scheduled optimally. The experimental analysis reveals that the hybrid algorithm comprising IRACE plus differential evolution offers statistically better results than the other algorithms when the budget of simulations is low. In contrast, IRACE performs better than the hybrids for a high simulations budget, although the optimization time is much longer.
    • URI
      https://hdl.handle.net/10630/27532
    • DOI
      https://dx.doi.org/10.1162/evco_a_00314
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    ECJ__Semaforos_extension_EvoCop_.pdf (864.3Kb)
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    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
     

     

    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA