Nsga-ii/sdr-ols: a novel large-scale many-objective optimization method using opposition-based learning and local search

HIGHLIGHTS

  • who: Yingxin Zhang et al. from the School of Computer Science and Technology, Ocean University of China, Qingdao, China have published the research work: NSGA-II/SDR-OLS: A Novel Large-Scale Many-Objective Optimization Method Using Opposition-Based Learning and Local Search, in the Journal: Mathematics 2023, 11, 1911. of /2023/
  • what: The authors compare the algorithm with six existing algorithms which are promising region-based multi-objective evolutionary algorithms (PREA) scalable small subpopulation-based covariance matrix adaptation evolution strategy (S3-CMA-ES) decomposition-based multi-objective evolutionary algorithm guided by growing neural gas . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?