Particle swarm optimization with spatially meaningful neighbours

Neighbourhood topologies in particle swarm optimization (PSO) are typically random in terms of the spatial positions of connected neighbours. This study explores the use of spatially meaningful neighbours for PSO. An approach is designed which uses heuristics to leverage the natural neighbours computed with Delaunay triangulation. The approach is compared to standard PSO sociometries and fitness distance ratio approaches. Although intrinsic properties of Delaunay triangulation limit the practical application of this approach to low dimensions results show that it is a successful particle swarm optimizer.

[1]  Jeff Erickson,et al.  Dense point sets have sparse Delaunay triangulations , 2001, ArXiv.

[2]  Russell C. Eberhart,et al.  Multiobjective optimization using dynamic neighborhood particle swarm optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[3]  Peter J. Bentley,et al.  Don't push me! Collision-avoiding swarms , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[4]  J. Kennedy,et al.  Neighborhood topologies in fully informed and best-of-neighborhood particle swarms , 2003, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[5]  Xiaodong Li,et al.  A multimodal particle swarm optimizer based on fitness Euclidean-distance ratio , 2007, GECCO '07.

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

[7]  Christian Posthoff,et al.  Randomized directed neighborhoods with edge migration in particle swarm optimization , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[8]  Mark Richards,et al.  Choosing a starting configuration for particle swarm optimization , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[9]  Rui Mendes,et al.  Neighborhood topologies in fully informed and best-of-neighborhood particle swarms , 2006 .

[10]  José Neves,et al.  What Makes a Successful Society? Experiments with Population Topologies in Particle Swarms , 2004, SBIA.

[11]  Kalyan Veeramachaneni,et al.  Optimization Using Particle Swarms with Near Neighbor Interactions , 2003, GECCO.

[12]  Jeff Erickson,et al.  Dense Point Sets Have Sparse Delaunay Triangulations or “... But Not Too Nasty” , 2001, SODA '02.

[13]  Dan Ventura,et al.  Dynamic Sociometry in Particle Swarm Optimization , 2003 .

[14]  P Cignoni,et al.  DeWall: A fast divide and conquer Delaunay triangulation algorithm in Ed , 1998, Comput. Aided Des..

[15]  Andries Petrus Engelbrecht,et al.  A Cooperative approach to particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[16]  Andries Petrus Engelbrecht,et al.  Locating multiple optima using particle swarm optimization , 2007, Appl. Math. Comput..

[17]  Leonidas J. Guibas,et al.  Kinetic data structures in practice , 2007 .

[18]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[19]  Jean-Philippe Pons,et al.  Spatio-Temporal Shape from Silhouette using Four-Dimensional Delaunay Meshing , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[20]  J. Kennedy,et al.  Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[21]  Christian Posthoff,et al.  Neighborhood Re-structuring in Particle Swarm Optimization , 2005, Australian Conference on Artificial Intelligence.

[22]  José Neves,et al.  The fully informed particle swarm: simpler, maybe better , 2004, IEEE Transactions on Evolutionary Computation.

[23]  T. Krink,et al.  Particle swarm optimisation with spatial particle extension , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[24]  P. Suganthan.  Particle swarm optimiser with neighbourhood operator , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[25]  James Kennedy,et al.  Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).