particle swarm optimization
Download
Skip this Video
Download Presentation
Particle Swarm Optimization

Loading in 2 Seconds...

play fullscreen
1 / 11

Particle Swarm Optimization - PowerPoint PPT Presentation


  • 211 Views
  • Uploaded on

Particle Swarm Optimization. James Kennedy & Russel C. Eberhart. Idea Originator. Landing of Bird Flocks Function Optimization Thinking is Social Collisions are allowed. Simple Model. Swarm of Particles Position in Solution Space New Position by Random Steps

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Particle Swarm Optimization' - sierra-bowen


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
particle swarm optimization

Particle Swarm Optimization

James Kennedy & Russel C. Eberhart

idea originator
Idea Originator
  • Landing of Bird Flocks
  • Function Optimization
  • Thinking is Social
  • Collisions are allowed
simple model
Simple Model
  • Swarm of Particles
  • Position in Solution Space
  • New Position by Random Steps
  • Direction towards current Optimum
  • Multi-Dimensional Functions
first feedbacks
First Feedbacks
  • Fast in Uni-Modal Functions
  • Neuronal-Network Training (9h to 3min)
  • Able to compete with GA (overhead)
  • But, Algorithm is based on Broadcasting
  • Multi-modal Function Optimization
algorithm updates
Algorithm Updates
  • Storage of individual Best [Kennedy]
  • Move between individual & global Best
  • Constriction Factor [Shi&Eberhart]
  • Tracking Changing Extreme [Carlisle]
hybrid pso
Hybrid PSO
  • Breed & Sub-population
  • Combine Adv. of PSO & EA
  • Anal. comparison PSO vs. GA [Angeline]
  • Idea: Increase Diversification
hybrid approach breeding
Hybrid Approach - Breeding
  • Steps

Select Breeding Population (pb – prob.)

Select two random Parents

Replace Parents by Offspring

  • Offspring Creation

arithmetic crossover for position & velocity

hybrid approach sub popul
Hybrid Approach – Sub-Popul.
  • Steps

Divide into multiple Subpopul.

Spread particles over solution space

Use Breeding approach

  • Sub-Popul. Selection

Breeding over diff. Poul. (psb – prob.)

hyb results
Hyb. Results
  • Usage of 4 multi-dim. Functions
  • In uni-modal function GA & std. PSO better
  • In multi-modal function hyp. PSO better

convergence & solution

  • Subpopulation results in no gains
conclusion
Conclusion
  • New Research Area

First PSO in 1995, First Conf. Last Year

  • Highly accepted

Increasing Research & Evol. Comp. Special

  • Can we learn from GA & PSO a improved method with reduced overhead?
reading room
Reading Room
  • “Swarm Intelligence”

by Kennedy & Eberhart [2001]

  • Bibliography

www.computelligence.org/pso/bibliography.htm

ad