A particle swarm optimization algorithm can optimize the problems with linear constraints, nonlinear constraints, equality constraints and bounded constraints. The method is similar to the GA algorithm of MATLAB

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

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