Surrogated-assisted multimodal multi-objective optimization for hybrid renewable energy system

HIGHLIGHTS

  • who: Tao Zhang from the College of Systems Engineering, National University of Defense Technology, Changsha, China have published the paper: Surrogated-assisted multimodal multi-objective optimization for hybrid renewable energy system, in the Journal: (JOURNAL)
  • what: Obtaining all Pareto solutions for MMOPs is difficult for traditional MOEAs due to the following reasons: the use of the convergence-first strategy to select a new generation will cause premature population; the crowding distance in the objective space will force the algorithm to remove solutions with similar objective values. To better address HRES, in this study, the authors . . .

     

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