What are the particles (code wise) in Particle / Genetical Swarm Optimization algorithm? -


edit hi, trying implement particle (or genetical) swarm optimization. however, stuck in first step...

i getting confused on how initialise particles, , these particles (in terms of code) are.

i've found various information on algorithm (on own) , implementation, didn't find information want...

can explain, please?

thanks.

andrea.

if familiar python, learned genetic algorithms , pso using deap. have excellent tutorials , docs.

definition: pso optimizes problem having population of candidate solutions, here dubbed particles, , moving these particles around in search-space according simple mathematical formulae. movements of particles guided best found positions in search-space updated better positions found particles.

what particle?

a particle has current position, velocity, , record of past positions. each particle has own velocity , position update rules.

how optimization search work?

you run algorithm given number of iterations. on each iteration update each particle's velocity , position. hope find best solution or solution enough.

concrete example.

imagine search objective find star. @ each iteration find particle closest finding star. move other particles in direction.

pso pic

image courtesy of wirelesstech


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