TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Hellwig, Michael
A1  - Beyer, Hans-Georg
T1  - A modified matrix adaptation evolution strategy with restarts for constrained real-world problems
T2  - 2020 IEEE Congress on Evolutionary Computation (CEC)
N2  - 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.
KW  - Optimization
KW  - Constraints
KW  - Evolutionary algorithms
Y1  - 2020
SN  - 978-1-7281-6929-3
SB  - 978-1-7281-6929-3
U6  - https://doi.org/10.1109/CEC48606.2020.9185566
DO  - https://doi.org/10.1109/CEC48606.2020.9185566
SP  - 8
S1  - 8
PB  - IEEE
CY  - Piscataway, NJ
ER  -