TY - JOUR
T1 - Particle swarm optimization with an aging leader and challengers
AU - Chen, Wei Neng
AU - Zhang, Jun
AU - Lin, Ying
AU - Chen, Ni
AU - Zhan, Zhi Hui
AU - Chung, Henry Shu Hung
AU - Li, Yun
AU - Shi, Yu Hui
PY - 2013/4/8
Y1 - 2013/4/8
N2 - In nature, almost every organism ages and has a limited lifespan. Aging has been explored by biologists to be an important mechanism for maintaining diversity. In a social animal colony, aging makes the old leader of the colony become weak, providing opportunities for the other individuals to challenge the leadership position. Inspired by this natural phenomenon, this paper transplants the aging mechanism to particle swarm optimization (PSO) and proposes a PSO with an aging leader and challengers (ALC-PSO). ALC-PSO is designed to overcome the problem of premature convergence without significantly impairing the fast-converging feature of PSO. It is characterized by assigning the leader of the swarm with a growing age and a lifespan, and allowing the other individuals to challenge the leadership when the leader becomes aged. The lifespan of the leader is adaptively tuned according to the leader's leading power. If a leader shows strong leading power, it lives longer to attract the swarm toward better positions. Otherwise, if a leader fails to improve the swarm and gets old, new particles emerge to challenge and claim the leadership, which brings in diversity. In this way, the concept 'aging' in ALC-PSO actually serves as a challenging mechanism for promoting a suitable leader to lead the swarm. The algorithm is experimentally validated on 17 benchmark functions. Its high performance is confirmed by comparing with eight popular PSO variants.
AB - In nature, almost every organism ages and has a limited lifespan. Aging has been explored by biologists to be an important mechanism for maintaining diversity. In a social animal colony, aging makes the old leader of the colony become weak, providing opportunities for the other individuals to challenge the leadership position. Inspired by this natural phenomenon, this paper transplants the aging mechanism to particle swarm optimization (PSO) and proposes a PSO with an aging leader and challengers (ALC-PSO). ALC-PSO is designed to overcome the problem of premature convergence without significantly impairing the fast-converging feature of PSO. It is characterized by assigning the leader of the swarm with a growing age and a lifespan, and allowing the other individuals to challenge the leadership when the leader becomes aged. The lifespan of the leader is adaptively tuned according to the leader's leading power. If a leader shows strong leading power, it lives longer to attract the swarm toward better positions. Otherwise, if a leader fails to improve the swarm and gets old, new particles emerge to challenge and claim the leadership, which brings in diversity. In this way, the concept 'aging' in ALC-PSO actually serves as a challenging mechanism for promoting a suitable leader to lead the swarm. The algorithm is experimentally validated on 17 benchmark functions. Its high performance is confirmed by comparing with eight popular PSO variants.
KW - aging
KW - global search
KW - leader
KW - particle swarm optimization (PSO)
KW - premature convergence
UR - http://www.scopus.com/inward/record.url?scp=84875736923&partnerID=8YFLogxK
U2 - 10.1109/TEVC.2011.2173577
DO - 10.1109/TEVC.2011.2173577
M3 - Article
AN - SCOPUS:84875736923
SN - 1089-778X
VL - 17
SP - 241
EP - 258
JO - IEEE Transactions on Evolutionary Computation
JF - IEEE Transactions on Evolutionary Computation
IS - 2
M1 - 6151121
ER -