TY - GEN
T1 - Problem difficulty analysis for particle swarm optimization
T2 - 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09
AU - Xin, Bin
AU - Chen, Jie
AU - Pan, Feng
PY - 2009
Y1 - 2009
N2 - This paper studies the problem difficulty for a popular optimization method - particle swarm optimization (PSO), particularly for the PSO variant PSO-cf (PSO with constriction factor), and analyzes its predictive measures. Some previous measures and related issues about other optimizers, mainly including deception and modality, are checked for PSO. It is observed that deception is mainly the combination of three factors - the measure ratios of attraction basins, the relative distance of attractors and the relative difference of attractors' altitudes. Multimodality and multi-funnel are proved not to be the essential factors contributing to the problem difficulty for PSO. The counterexamples and comparative experiments in this paper can be taken as a reference for further researches on novel comprehensive predictive measures of problem difficulty for PSO.
AB - This paper studies the problem difficulty for a popular optimization method - particle swarm optimization (PSO), particularly for the PSO variant PSO-cf (PSO with constriction factor), and analyzes its predictive measures. Some previous measures and related issues about other optimizers, mainly including deception and modality, are checked for PSO. It is observed that deception is mainly the combination of three factors - the measure ratios of attraction basins, the relative distance of attractors and the relative difference of attractors' altitudes. Multimodality and multi-funnel are proved not to be the essential factors contributing to the problem difficulty for PSO. The counterexamples and comparative experiments in this paper can be taken as a reference for further researches on novel comprehensive predictive measures of problem difficulty for PSO.
KW - Global optimization
KW - Particle swarm optimization
KW - Problem hardness
UR - http://www.scopus.com/inward/record.url?scp=67650649984&partnerID=8YFLogxK
U2 - 10.1145/1543834.1543919
DO - 10.1145/1543834.1543919
M3 - Conference contribution
AN - SCOPUS:67650649984
SN - 9781605583266
T3 - 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09
SP - 623
EP - 630
BT - 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09
Y2 - 12 June 2009 through 14 June 2009
ER -