TY - GEN
T1 - Brain storm optimization algorithm
AU - Shi, Yuhui
PY - 2011
Y1 - 2011
N2 - Human being is the most intelligent animal in this world. Intuitively, optimization algorithm inspired by human being creative problem solving process should be superior to the optimization algorithms inspired by collective behavior of insects like ants, bee, etc. In this paper, we introduce a novel brain storm optimization algorithm, which was inspired by the human brainstorming process. Two benchmark functions were tested to validate the effectiveness and usefulness of the proposed algorithm.
AB - Human being is the most intelligent animal in this world. Intuitively, optimization algorithm inspired by human being creative problem solving process should be superior to the optimization algorithms inspired by collective behavior of insects like ants, bee, etc. In this paper, we introduce a novel brain storm optimization algorithm, which was inspired by the human brainstorming process. Two benchmark functions were tested to validate the effectiveness and usefulness of the proposed algorithm.
KW - Brain Storm Optimization
KW - Brainstorming Process
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=79958194494&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21515-5_36
DO - 10.1007/978-3-642-21515-5_36
M3 - Conference Proceeding
AN - SCOPUS:79958194494
SN - 9783642215148
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 303
EP - 309
BT - Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings
T2 - 2nd International Conference on Swarm Intelligence, ICSI 2011
Y2 - 12 June 2011 through 15 June 2011
ER -