TY - GEN
T1 - A new strategy for finding good local guides in MOPSO
AU - Leung, Man Fai
AU - Ng, Sin Chun
AU - Cheung, Chi Chung
AU - Lui, Andrew K.
PY - 2014/7/6
Y1 - 2014/7/6
N2 - This paper presents a new algorithm that extends Particle Swarm Optimization (PSO) to deal with multi-objective problems. It makes two main contributions. The first is that the square root distance (SRD) computation among particles and leaders is proposed to be the criterion of the local best selection. This new criterion can make all swarms explore the whole Pareto-front more uniformly. The second contribution is the procedure to update the archive members. When the external archive is full and a new member is to be added, an existing archive member with the smallest SRD value among its neighbors will be deleted. With this arrangement, the non-dominated solutions can be well distributed. Through the performance investigation, our proposed algorithm performed better than two well-known multi-objective PSO algorithms, MOPSO-σ and MOPSO-CD, in terms of different standard measures.
AB - This paper presents a new algorithm that extends Particle Swarm Optimization (PSO) to deal with multi-objective problems. It makes two main contributions. The first is that the square root distance (SRD) computation among particles and leaders is proposed to be the criterion of the local best selection. This new criterion can make all swarms explore the whole Pareto-front more uniformly. The second contribution is the procedure to update the archive members. When the external archive is full and a new member is to be added, an existing archive member with the smallest SRD value among its neighbors will be deleted. With this arrangement, the non-dominated solutions can be well distributed. Through the performance investigation, our proposed algorithm performed better than two well-known multi-objective PSO algorithms, MOPSO-σ and MOPSO-CD, in terms of different standard measures.
UR - http://www.scopus.com/inward/record.url?scp=84908584285&partnerID=8YFLogxK
U2 - 10.1109/CEC.2014.6900449
DO - 10.1109/CEC.2014.6900449
M3 - Conference article published in proceeding or book
AN - SCOPUS:84908584285
T3 - Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
SP - 1990
EP - 1997
BT - Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE Congress on Evolutionary Computation, CEC 2014
Y2 - 6 July 2014 through 11 July 2014
ER -