TY - GEN
T1 - Brain storm optimization algorithm with re-initialized ideas and adaptive step size
AU - El-Abd, Mohammed
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/14
Y1 - 2016/11/14
N2 - Brain Storm Optimization (BSO) is a recently developed population-based algorithm to mimic the brainstorming process in humans. It has been successfully applied in the domain of non-linear continuous optimization. In this work, we propose enhancing the performance of BSO by introducing a re-initialization mechanism triggered by the current state of the population. In addition, we also propose to modify the step-size equation in order to take the search space size into consideration. The proposed improved BSO is compared with two of the most recent BSO variants based on the CEC15 benchmarks.
AB - Brain Storm Optimization (BSO) is a recently developed population-based algorithm to mimic the brainstorming process in humans. It has been successfully applied in the domain of non-linear continuous optimization. In this work, we propose enhancing the performance of BSO by introducing a re-initialization mechanism triggered by the current state of the population. In addition, we also propose to modify the step-size equation in order to take the search space size into consideration. The proposed improved BSO is compared with two of the most recent BSO variants based on the CEC15 benchmarks.
UR - https://www.scopus.com/pages/publications/85008259382
U2 - 10.1109/CEC.2016.7744125
DO - 10.1109/CEC.2016.7744125
M3 - Conference contribution
T3 - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
SP - 2682
EP - 2686
BT - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
Y2 - 24 July 2016 through 29 July 2016
ER -