TY - GEN
T1 - Hybrid cooperative co-evolution for the CEC15 benchmarks
AU - El-Abd, Mohammed
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/10
Y1 - 2015/9/10
N2 - In this paper, we test the performance of hybrid cooperative co-evolution (hCC) on the CEC15 benchmarks. In its initial stage, the method applies the recently introduced differential grouping to learn the problem variables' inter-dependencies and separate the variables into groups of separable and non-separable ones. In its second stage, the method adopts different algorithms within the cooperative co-evolution (CC) framework to simultaneously optimize the generated groups. Results are reported for all required problem sizes.
AB - In this paper, we test the performance of hybrid cooperative co-evolution (hCC) on the CEC15 benchmarks. In its initial stage, the method applies the recently introduced differential grouping to learn the problem variables' inter-dependencies and separate the variables into groups of separable and non-separable ones. In its second stage, the method adopts different algorithms within the cooperative co-evolution (CC) framework to simultaneously optimize the generated groups. Results are reported for all required problem sizes.
UR - https://www.scopus.com/pages/publications/84963517844
U2 - 10.1109/CEC.2015.7257006
DO - 10.1109/CEC.2015.7257006
M3 - Conference contribution
T3 - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
SP - 1053
EP - 1058
BT - 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE Congress on Evolutionary Computation, CEC 2015
Y2 - 25 May 2015 through 28 May 2015
ER -