抄録
Particle Swarm Optimization(PSO) is widely used in optimization problems, due to its powerful search ability and easy implementation. Recently, multi-objective PSO is introduced to deal with multi-objective optimization problems.
There are two differences from single objective PSO.
One is an archive that preserves Pareto optimal candidates,
and the other is selection strategies for the guide particles, such as the personal best and the global best.
In this paper, based on particle topology we propose a novel strategy in guide selection in multi-objective PSO.
Numerical simulation results show the availability of the proposed method in several benchmark problems.
