Confinements and Biases in Particle Swarm Optimisation

All PSO versions do present one or more biases, often in favor of the center of the search space. An important factor that induces such biases is the method used to keep particles inside the search space. We compare here nine methods on a few benchmark functions, and the results suggest another one which is less biased. Furthermore this study also suggests how to adaptively modify the search space for each move. Thanks to these two simple modifications the resulting PSO is both more robust and more effective.

[1]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[2]  Kevin D. Seppi,et al.  Exposing origin-seeking bias in PSO , 2005, GECCO '05.

[3]  M. Clerc,et al.  Particle Swarm Optimization , 2006 .