Carlos Artemio Coello Coello

Group Leader

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Information of interest

  • Multiple source transfer learning for dynamic multiobjective optimization 

    Ye, Y.; Lin, Q.; Ma, L.; Wong, K. C.; Gong, M.; Coello, C.A.Autoridad BCAM (2022-08-01)
    Recently, dynamic multiobjective evolutionary algorithms (DMOEAs) with transfer learning have become popular for solving dynamic multiobjective optimization problems (DMOPs), as the used transfer learning methods in DMOEAs ...
  • A Novel Parametric benchmark generator for dynamic multimodal optimization 

    Ahrari, A.; Elsayed, S.; Sarker, R.; Essam, D.; Coello, C.A.Autoridad BCAM (2021-08-01)
    In most existing studies on dynamic multimodal optimization (DMMO), numerical simulations have been performed using the Moving Peaks Benchmark (MPB), which is a two-decade-old test suite that cannot simulate some critical ...
  • On the Construction of Pareto-Compliant Combined Indicators 

    Falcón-Cardona, J.G.; Emmerich, M.; Coello, C.A.Autoridad BCAM (2022-08-12)
    The most relevant property that a quality indicator (QI) is expected to have is Pareto compliance, which means that every time an approximation set strictly dominates another in a Pareto sense, the indicator must reflect ...
  • Parallel Multi-Objective Evolutionary Algorithms: A Comprehensive Survey 

    Falcón-Cardona, J.G.; Hernández Gómez, R.; Coello, C.A.Autoridad BCAM; Castillo Tapia, M.G. (2021-12-01)
    Multi-Objective Evolutionary Algorithms (MOEAs) are powerful search techniques that have been extensively used to solve difficult problems in a wide variety of disciplines. However, they can be very demanding in terms of ...

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