@inproceedings{HellwigBeyer2020,
  author    = {Michael Hellwig and Hans-Georg Beyer},
  title     = {A modified matrix adaptation evolution strategy with restarts for constrained real-world problems},
  series = {2020 IEEE Congress on Evolutionary Computation (CEC)},
  publisher = {IEEE},
  address   = {Piscataway, NJ},
  isbn      = {978-1-7281-6929-3},
  doi       = {10.1109/CEC48606.2020.9185566},
  year      = {2020},
  abstract  = {In combination with successful constraint handling techniques, a Matrix Adaptation Evolution Strategy (MA-ES) variant (the εMAg-ES) turned out to be a competitive algorithm on the constrained optimization problems proposed for the CEC 2018 competition on constrained single objective real-parameter optimization. A subsequent analysis points to additional potential in terms of robustness and solution quality. The consideration of a restart scheme and adjustments in the constraint handling techniques put this into effect and simplify the configuration. The resulting BP-εMAg-ES algorithm is applied to the constrained problems proposed for the IEEE CEC 2020 competition on Real-World Single-Objective Constrained optimization. The novel MA-ES variant realizes improvements over the original εMAg-ES in terms of feasibility and effectiveness on many of the real-world benchmarks. The BP-εMAg-ES realizes a feasibility rate of 100\% on 44 out of 57 real-world problems and improves the best-known solution in 5 cases.},
  language  = {en}
}