TY - GEN
T1 - Promoting diversity in particle swarm optimization to solve multimodal problems
AU - Cheng, Shi
AU - Shi, Yuhui
AU - Qin, Quande
N1 - Funding Information:
The authors’ work was supported by National Natural Science Foundation of China under grant No. 60975080, and Suzhou Science and Technology Project under Grant No. SYJG0919.
PY - 2011
Y1 - 2011
N2 - Promoting diversity is an effective way to prevent premature converge in solving multimodal problems using Particle Swarm Optimization (PSO). Based on the idea of increasing possibility of particles "jump out" of local optima, while keeping the ability of algorithm finding "good enough" solution, two methods are utilized to promote PSO's diversity in this paper. PSO population diversity measurements, which include position diversity, velocity diversity and cognitive diversity on standard PSO and PSO with diversity promotion, are discussed and compared. Through this measurement, useful information of search in exploration or exploitation state can be obtained.
AB - Promoting diversity is an effective way to prevent premature converge in solving multimodal problems using Particle Swarm Optimization (PSO). Based on the idea of increasing possibility of particles "jump out" of local optima, while keeping the ability of algorithm finding "good enough" solution, two methods are utilized to promote PSO's diversity in this paper. PSO population diversity measurements, which include position diversity, velocity diversity and cognitive diversity on standard PSO and PSO with diversity promotion, are discussed and compared. Through this measurement, useful information of search in exploration or exploitation state can be obtained.
KW - Particle swarm optimization
KW - diversity promotion
KW - exploration/exploitation
KW - multimodal problems
KW - population diversity
UR - http://www.scopus.com/inward/record.url?scp=81855174486&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24958-7_27
DO - 10.1007/978-3-642-24958-7_27
M3 - Conference Proceeding
AN - SCOPUS:81855174486
SN - 9783642249570
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 228
EP - 237
BT - Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
T2 - 18th International Conference on Neural Information Processing, ICONIP 2011
Y2 - 13 November 2011 through 17 November 2011
ER -