TY - CHAP
T1 - A double particle swarm optimization for mixed-variable optimization problems
AU - Sun, Chaoli
AU - Zeng, Jianchao
AU - Pan, Jengshyang
AU - Chu, Shuchuan
AU - Zhang, Yunqiang
PY - 2011/9/7
Y1 - 2011/9/7
N2 - A double particle swarm optimization (DPSO), in which MPSO proposed by Sun et al. [1] is used as a global search algorithm and PSO with feasibility-based rules is used to do local searching, is proposed in this paper to solve mixed-variable optimization problems. MPSO can solve the non-continuous variables very well. However, the imprecise values of continuous variables brought the inconsistent results of each run. A particle swarm optimization with feasibility-based rules is proposed to find optimal values of continuous variables after the MPSO algorithm finishes each independent run, in order to obtain the consistent optimal results for mixed-variable optimization problems. The performance of DPSO is evaluated against two real-world mixed-variable optimization problems, and it is found to be highly competitive compared with other existing algorithms.
AB - A double particle swarm optimization (DPSO), in which MPSO proposed by Sun et al. [1] is used as a global search algorithm and PSO with feasibility-based rules is used to do local searching, is proposed in this paper to solve mixed-variable optimization problems. MPSO can solve the non-continuous variables very well. However, the imprecise values of continuous variables brought the inconsistent results of each run. A particle swarm optimization with feasibility-based rules is proposed to find optimal values of continuous variables after the MPSO algorithm finishes each independent run, in order to obtain the consistent optimal results for mixed-variable optimization problems. The performance of DPSO is evaluated against two real-world mixed-variable optimization problems, and it is found to be highly competitive compared with other existing algorithms.
KW - feasibility-based rules
KW - mixed-variable optimization problems
KW - Particle swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=80052321847&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23418-7_9
DO - 10.1007/978-3-642-23418-7_9
M3 - Chapter
AN - SCOPUS:80052321847
SN - 9783642234170
VL - 381
T3 - Studies in Computational Intelligence
SP - 93
EP - 102
BT - Semantic Methods for Knowledge Management and Communication
A2 - Katarzyniak, Radoslaw
A2 - Nguyen, Ngoc Thanh
A2 - Chiu, Tzu-Fu
A2 - Hong, Chao-Fu
CY - Berlin
ER -