资源简介
本资料为研究生课程智能优化算法之粒子群优化算法部分的资料,包括代码,经典论文,以及授课PPT,对初学者非常有用
代码片段和文件信息
% demopsobehavior.m
% demo of the pso.m function
% the pso tries to find the minimum of the f6 function a standard
% benchmark
%
% on the plots blue is current position green is Pbest and red is Gbest
% Brian Birge
% Rev 3.0
% 2/27/06
clear all
close all
clc
help demopsobehavior
warning off
functnames = {‘ackley‘‘alpine‘‘DeJong_f2‘‘DeJong_f3‘‘DeJong_f4‘...
‘Foxhole‘‘Griewank‘‘NDparabola‘...
‘Rastrigin‘‘Rosenbrock‘‘f6‘‘f6mod‘‘tripod‘...
‘f6_bubbles_dyn‘‘f6_linear_dyn‘‘f6_spiral_dyn‘};
disp(‘Static test functions minima don‘‘t change w.r.t. time/iteration:‘);
disp(‘ 1) Ackley‘);
disp(‘ 2) Alpine‘);
disp(‘ 3) DeJong_f2‘);
disp(‘ 4) DeJong_f3‘);
disp(‘ 5) DeJong_f4‘);
disp(‘ 6) Foxhole‘);
disp(‘ 7) Griewank‘);
disp(‘ 8) NDparabola (for this demo N = 2)‘);
disp(‘ 9) Rastrigin‘);
disp(‘10) Rosenbrock‘);
disp(‘11) Schaffer f6‘);
disp(‘12) Schaffer f6 modified (5 f6 functions translated from each other)‘);
disp(‘13) Tripod‘);
disp(‘ ‘);
disp(‘Dynamic test functions minima/environment evolves over time/iteration:‘);
disp(‘14) f6_bubbles_dyn‘);
disp(‘15) f6_linear_dyn‘);
disp(‘16) f6_spiral_dyn‘);
functchc=input(‘Choose test function ? ‘);
functname = functnames{functchc};
disp(‘ ‘);
disp(‘1) Intense graphics shows error topology and surfing particles‘);
disp(‘2) Default PSO graphing shows error trend and particle dynamics‘);
disp(‘3) no plot only final output shown fastest‘);
plotfcn=input(‘Choose plotting function ? ‘);
if plotfcn == 1
plotfcn = ‘goplotpso4demo‘;
shw = 1; % how often to update display
elseif plotfcn == 2
plotfcn = ‘goplotpso‘;
shw = 1; % how often to update display
else
plotfcn = ‘goplotpso‘;
shw = 0; % how often to update display
end
% set flag for ‘dynamic function on‘ only used at very end for tracking plots
dyn_on = 0;
if functchc==15 | functchc == 16 | functchc == 17
dyn_on = 1;
end
%xrng=input(‘Input search range for X e.g. [-1010] ? ‘);
%yrng=input(‘Input search range for Y ? ‘);
xrng=[-3030];
yrng=[-4040];
disp(‘ ‘);
% if =0 then we look for minimum =1 then max
disp(‘0) Minimize‘)
disp(‘1) Maximize‘)
minmax=input(‘Choose search goal ?‘);
% minmax=0;
disp(‘ ‘);
mvden = input(‘Max velocity divisor (2 is a good choice) ? ‘);
disp(‘ ‘);
ps = input(‘How many particles (24 - 30 is common)? ‘);
disp(‘ ‘);
disp(‘0) Common PSO - with inertia‘);
disp(‘1) Trelea model 1‘);
disp(‘2) Trelea model 2‘);
disp(‘3) Clerc Type 1“ - with constriction‘);
modl = input(‘Choose PSO model ? ‘);
% note: if errgoal=NaN then unconstrained min or max is performed
if minmax==1
% errgoal=0.97643183; % max for f6 function (close enough for termination)
errgoal=NaN;
else
% errgoal=0; % min
errgoal=NaN;
end
minx = xrng(1);
maxx = xrng(2);
miny = yrng(1);
maxy = yrng(2);
%----
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