[CC BY-NC-SA 3.0] 2013 Blanca Rosa Cases, Maider Gaztelu and Abdelmalik Moujahid, University of the Basque Country
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The model implements some Particle Swarm Optimization (PSO) algorithms.
PSO is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of birds flying. The system is initialized with a population of potential solutions, called particles, who fly through the problem space by following the current optimum particles.
In this NetLogo model, the turtles simulate the fly of that population of particles.
The basic PSO model is the one called “STATIC-INERTIA”. Also some variants of the PSO basic model are provided. Then, in this NetLogo model you can see how different models of PSO works. This variants of PSO make changes in the initialization and updating of the ‘inertia weight (w)’, other fly parameters like ’c1’and ‘c2’ and also in the velocity and position equations.
1- Press Reset
2- Select a model in ‘the model’
3- Press ‘load-model’
4- Choose an objetive function in ‘function’
5- Press ‘SETUP-default-values’
6- (optional) Change settings of ‘Experiment Settings’ and then press ‘SETUP-own-values’
7- Run the model with ‘run’(all iterations) or with ‘1 step’(one iteration)
8- See results in section ‘Results’
Before that, you can make another experiment:
-The same PSO model, the same function –> repeat from step 5(to change experiment settings) or repeat from step 7(not to change experiment)
-The same PSO model, another function –> repeat from step 4
-Another PSO model –> repeat from step 1
Using the provided basic model of PSO, you can implement new different PSO models as we have made in ‘the-Model’ and expand the application.
Based on the algorithms presented in the following papers:
If you mention this model in a publication, we ask that you include these citations for the model itself and for the NetLogo software:
[CC BY-NC-SA 3.0] 2013 Blanca Rosa Cases, Maider Gaztelu and Abdelmalik Moujahid, University of the Basque Country
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/.