Constrained Particle Swarm Optimization
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Mudasser Seraj
el 20 de Feb. de 2018
Comentada: Walter Roberson
el 22 de Abr. de 2022
Hi,
I have 'N' particles with one-dimensional variable a(=accelration). However, each particle has a different range (lower limit, upper limit). If I want to use PSO to optimize the cost function which includes v (=valocity) and p (=postion) and inequality constraint of [position(N) - position (N-1) >= some value], then how should I do it?
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Walter Roberson
el 20 de Feb. de 2018
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Danish Ali
el 22 de Abr. de 2022
Dear Walter,@Walter Roberson
Thank you. However, this code doesn't run well as compare to genetic algorithm. Is there any way, we can improve the results (I have tried Hybrid function too) ? Any suggestions will be appreciated.
Walter Roberson
el 22 de Abr. de 2022
Is there mathematical reason to expect that particle swarm algorithms will run about as well as genetic algorithm in all cases? Or is there a restricted set of situations in which particle swarm is expected to be as good or better, and if so then does your particular situation fit within those cases?
When the only constraints are LB and UB, then particleswarm() handles that. https://www.mathworks.com/help/gads/particleswarm.html
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