# Population structure and particle swarm performance

@article{Kennedy2002PopulationSA, title={Population structure and particle swarm performance}, author={James Kennedy and Rui Mendes}, journal={Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)}, year={2002}, volume={2}, pages={1671-1676 vol.2} }

The effects of various population topologies on the particle swarm algorithm were systematically investigated. Random graphs were generated to specifications, and their performance on several criteria was compared. What makes a good population structure? We discovered that previous assumptions may not have been correct.

## 1,576 Citations

Particle swarm and population structure

- MathematicsGECCO
- 2018

The main conclusion is that regular and random graphs with the same averaged connectivity k may result in significantly different performance, namely when k is low.

Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms

- Computer ScienceProceedings of the 2003 IEEE International Workshop on Soft Computing in Industrial Applications, 2003. SMCia/03.
- 2003

We vary the way an individual in the particle swarm interacts with its neighbors. Performance depends on population topology as well as algorithm version.

In Search of the Essential Particle Swarm

- Geology2006 IEEE International Conference on Evolutionary Computation
- 2006

The particle swarm algorithm is broken down into its essential steps, and alternative interpretations of those steps are proposed. New versions that perform well on a suite of test functions are…

Choosing a starting configuration for particle swarm optimization

- Computer Science2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
- 2004

The work suggests the use of generators from centroidal Voronoi tessellations as the starting points for the swarm, and results suggest that CVT initialization improves PSO performance in high dimensional spaces.

Neighborhood topologies in fully informed and best-of-neighborhood particle swarms

- Computer ScienceIEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
- 2006

It appears that a fully informed particle swarm is more susceptible to alterations in the topology, but with a goodTopology, it can outperform the canonical version.

Neighborhood topologies in fully informed and best-of-neighborhood particle swarms

- Computer ScienceIEEE Trans. Syst. Man Cybern. Syst.
- 2006

It appears that a fully informed particle swarm is more susceptible to alterations in the topology, but with a goodTopology, it can outperform the canonical version.

Asynchronous Particle Swarm Optimization

- Mathematics, Computer Science2007 IEEE 15th Signal Processing and Communications Applications
- 2007

An asynchronous particle swarm optimization algorithm that can update their estimates independently and time delays are also allowed in obtaining information from their neighbors.

Particle Swarm Optimization With Dynamic Neighborhood

- Computer Science, Mathematics2007 IEEE 15th Signal Processing and Communications Applications
- 2007

This article considers probabilistic and distance based approaches for determining the neighbors of the particles and represents the dynamic neighborhood topology by a time varying graph.

A Statistical Study of the Effects of Neighborhood Topologies in Particle Swarm Optimization

- Computer Science
- 2011

Particle swarm optimization (PSO) is a meta-heuristic which has been found to be very successful in a wide variety of optimization tasks.

Particle Swarm Optimization with Chaos-based Initialization for Numerical Optimization

- Computer Science, Physics
- 2018

Particle swarm optimization (PSO) is a population based swarm intelligence algorithm that has been deeply studied and widely applied to a variety of problems. However, it is easily trapped into the...

## References

SHOWING 1-10 OF 11 REFERENCES

Parameter Selection in Particle Swarm Optimization

- Computer ScienceEvolutionary Programming
- 1998

This paper first analyzes the impact that inertia weight and maximum velocity have on the performance of the particle swarm optimizer, and then provides guidelines for selecting these two parameters.…

Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance

- Computer ScienceProceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406)
- 1999

The study manipulated the neighborhood topologies of particle swarms optimizing four test functions and Sociometric structure and the small-world manipulation interacted with function to produce a significant effect on performance.

Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences

- Computer ScienceEvolutionary Programming
- 1998

This paper investigates the philosophical and performance differences of particle swarm and evolutionary optimization by comparison experiments involving four non-linear functions well studied in the evolutionary optimization literature.

The particle swarm - explosion, stability, and convergence in a multidimensional complex space

- Computer ScienceIEEE Trans. Evol. Comput.
- 2002

This paper analyzes a particle's trajectory as it moves in discrete time, then progresses to the view of it in continuous time, leading to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies.

Knowledge-based self-adaptation in evolutionary programming using cultural algorithms

- Computer ScienceProceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97)
- 1997

The results suggest that the use of a cultural framework for self-adaptation in EP can produce substantial performance improvements as expressed in terms of CPU time.

Particle swarm optimization: surfing the waves

- Computer ScienceProceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406)
- 1999

This paper takes the next step, generalizing to obtain closed form equations for trajectories of particles in a multi-dimensional search space.

Collective dynamics of ‘small-world’ networks

- Computer ScienceNature
- 1998

Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.

Adaptation in natural and artificial systems

- Computer Science
- 1975

Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.

Small worlds: the dynamics of networks between order and randomness

- Computer ScienceSGMD
- 2002

Everyone knows the small-world phenomenon: soon after meeting a stranger, we are surprised to discover that we have a mutual friend, or we are connected through a short chain of acquaintances. In his…

Collective dynamics of ‘small-world

- L L
- 1998