Particle swarm optimization is a derivative-free global optimum search algorithm based on the collective intelligence of a large group of intercommunicating entities. The individual particles are simple and primitive, knowing only their own current locations and fitness values, their personal best locations, and the swarm s best location. Each particle continually adjusts its trajectory based this information, moving towards the global optimum with each iteration. The swarm as a whole displays a remarkable level of coherence and coordination despite the simplicity of its individual particles. The coordinated behavior of the swarm has been compared with that of a flock of birds or a school of fish.

license.txt
psopt
.....\license.txt
.....\private
.....\.......\heart.m
.....\.......\initstate.m
.....\.......\overlaycontour.m
.....\.......\overlaysurface.m
.....\.......\psocheckbounds.m
.....\.......\psocheckinitialpopulation.m
.....\.......\psocheckpopulationinitrange.m
.....\.......\psocreationbinary.m
.....\.......\psocreationuniform.m
.....\.......\psogenerateoutputmessage.m
.....\.......\psogetinitialpopulation.m
.....\.......\psoiterate.m
.....\.......\psorunhybridfcn.m
.....\.......\quadrifolium.m
.....\.......\unitcircle.m
.....\.......\unitdisk.m
.....\.......\void.m
.....\pso.m
.....\psocalculatepenalties.m
.....\psodemo.m
.....\psooptimset.m
.....\psoplotbestf.m
.....\psoplotscorediversity.m
.....\psoplotswarm.m
.....\psoplotswarmsurf.m
.....\releasenotes.txt
.....\testfcns
.....\........\ackleysfcn.m
.....\........\binarytestfcn.m
.....\........\dejongsfcn.m
.....\........\dropwavefcn.m
.....\........\griewangksfcn.m
.....\........\langermannsfcn.m
.....\........\nonlinearconstrdemo.m
.....\........\rastriginsfcn.m
.....\........\rosenbrocksfcn.m
.....\........\schwefelsfcn.m
.....\........\templatefcn.m
.....\........\testfcn1.m

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