The genetic algorithm and particle swarm algorithm are used to find the maximum value of the function, and the performance of the two algorithms is compared. The running time and the number of iterations are used to judge

粒子群优化\fun.m
..........\ga\bs2rv.m
..........\..\contents.m
..........\..\crtbase.m
..........\..\crtbp.m
..........\..\crtrp.m
..........\..\DOC\GATBXA0.PS
..........\..\...\GATBXA1.PS
..........\..\...\GATBXA2.PS
..........\..\gpl.txt
..........\..\migrate.m
..........\..\mpga.m
..........\..\mut.m
..........\..\mutate.m
..........\..\mutbga.m
..........\..\objfun1.m
..........\..\objharv.m
..........\..\ranking.m
..........\..\recdis.m
..........\..\recint.m
..........\..\reclin.m
..........\..\recmut.m
..........\..\recombin.m
..........\..\reins.m
..........\..\rep.m
..........\..\resplot.m
..........\..\rws.m
..........\..\scaling.m
..........\..\select.m
..........\..\sga.m
..........\..\sus.m
..........\..\Test_fns\demoga1.M
..........\..\........\mpga.M
..........\..\........\objbran.M
..........\..\........\objdopi.M
..........\..\........\objeaso.M
..........\..\........\objfun1.M
..........\..\........\objfun1a.M
..........\..\........\objfun1b.M
..........\..\........\objfun2.M
..........\..\........\objfun6.M
..........\..\........\objfun7.M
..........\..\........\objfun8.M
..........\..\........\objfun9.M
..........\..\........\objgold.M
..........\..\........\objharv.M
..........\..\........\objlinq.M
..........\..\........\objlinq2.M
..........\..\........\objpush.M
..........\..\........\objsixh.M
..........\..\........\resplot.M
..........\..\........\sga.M
..........\..\........\simdopi1.M
..........\..\........\simdopi2.M
..........\..\........\simlinq1.M
..........\..\........\simlinq2.M
..........\..\........\simobjp.M
..........\..\........\TEST_FNS.PS
..........\..\xovdp.m
..........\..\xovdprs.m
..........\..\xovmp.m
..........\..\xovsh.m
..........\..\xovshrs.m
..........\..\xovsp.m
..........\..\xovsprs.m
..........\ga.m
..........\pso.m
..........\粒子群算法工具箱\A Particle Swarm Optimization (PSO) Primer.pdf
..........\................\DemoPSOBehavior.m
..........\................\goplotpso.m
..........\................\goplotpso4demo.m
..........\................\hiddenutils\forcecol.m
..........\................\...........\forcerow.m
..........\................\...........\linear_dyn.m
..........\................\...........\normmat.m
..........\................\...........\spiral_dyn.m
..........\................\nnet\demoPSOnet.m
..........\................\....\goplotpso4net.m
..........\................\....\pso_neteval.m
..........\................\....\trainpso.m
..........\................\pso_Trelea_vectorized.m
..........\................\PSO工具箱使用简介.doc
..........\................\ReadME.txt
..........\................\testfunctions\ackley.m
..........\................\.............\alpine.m
..........\................\.............\DeJong_f2.m
..........\................\.............\DeJong_f3.m
..........\................\.............\DeJong_f4.m
..........\................\.............\f6.m
..........\................\.............\f6mod.m
..........\................\.............\f6_bubbles_dyn.m
..........\................\.............\f6_linear_dyn.m
..........\................\.............\f6_spiral_dyn.m
..........\................\.............\Foxhole.m
..........\................\.............\Griewank.m
..........\................\.............\NDparabola.m
..........\................\.............\Rastrigin.m
..........\................\.............\Rosenbrock.m
..........\................\.............\tripod.m
..........\................\test_func.m

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