TY - JOUR
T1 - A Hybrid Particle Swarm Optimization Algorithm Based on Space Transformation Search and a Modified Velocity Model
AU - S. Yu, Z. Wu, H. Wang, Z. Chen & H. Zhong
JO - International Journal of Numerical Analysis and Modeling
VL - 2
SP - 371
EP - 377
PY - 2012
DA - 2012/09
SN - 9
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/ijnam/634.html
KW - Space Transformation Search (STS), evolutionary algorithm, Particle Swarm Optimization (PSO), optimization.
AB - <p style="text-align: justify;">Particle Swarm Optimization (PSO) has shown its fast search speed in many complicated
optimization and search problems. However, PSO often easily falls into local optima
because the particles would quickly get closer to the best particle. Under these circumstances,
the best particle could hardly be improved. This paper proposes a new hybrid PSO (HPSO) to
solve this problem by combining space transformation search (STS) with a new modified velocity
model. Experimental studies on 8 benchmark functions demonstrate that the HPSO holds good
performance in solving both unimodal and multimodal functions optimization problems.</p>