资源简介
This is a Hybrid PSO GSA Aigorithm.A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The main idea is to integrate the ability of exploitation in PSO with the ability of explora
代码片段和文件信息
%PSOGSA source code v3.0 Generated by SeyedAli Mirjalili 2011.
%Adopted from: S. Mirjalili S.Z. Mohd Hashim 揂 New Hybrid PSOGSA
%Algorithm for Function Optimization in IEEE International Conference
%on Computer and Information Application?ICCIA 2010) China 2010 pp.374-377.
% This function calculates the value of objective function.
function fit=benchmark_functions(LBenchmark_Function_IDdim)
%You can insert your own objective function with a new Benchmark_Function_ID.
if Benchmark_Function_ID==1
fit=sum(L.^2);
end
if Benchmark_Function_ID==2
fit=sum(abs(L))+prod(abs(L));
end
if Benchmark_Function_ID==3
fit=0;
for i=1:dim
fit=fit+sum(L(1:i))^2;
end
end
if Benchmark_Function_ID==4
fit=max(abs(L));
end
if Benchmark_Function_ID==5
fit=sum(100*(L(2:dim)-(L(1:dim-1).^2)).^2+(L(1:dim-1)-1).^2);
end
if Benchmark_Function_ID==6
fit=sum(abs((L+.5)).^2);
end
if Benchmark_Function_ID==7
fit=sum([1:dim].*(L.^4))+rand;
end
if Benchmark_Function_ID==8
fit=sum(-L.*sin(sqrt(abs(L))));
end
if Benchmark_Function_ID==9
fit=sum(L.^2-10*cos(2*pi.*L))+10*dim;
end
if Benchmark_Function_ID==10
fit=-20*exp(-.2*sqrt(sum(L.^2)/dim))-exp(sum(cos(2*pi.*L))/dim)+20+exp(1);
end
if Benchmark_Function_ID==11
fit=sum(L.^2)/4000-prod(cos(L./sqrt([1:dim])))+1;
end
if Benchmark_Function_ID==12
fit=(pi/dim)*(10*((sin(pi*(1+(L(1)+1)/4)))^2)+sum((((L(1:dim-1)+1)./4).^2).*...
(1+10.*((sin(pi.*(1+(L(2:dim)+1)./4)))).^2))+((L(dim)+1)/4)^2)+sum(Ufun(L101004));
end
if Benchmark_Function_ID==13
fit=.1*((sin(3*pi*L(1)))^2+sum((L(1:dim-1)-1).^2.*(1+(sin(3.*pi.*L(2:dim))).^2))+...
((L(dim)-1)^2)*(1+(sin(2*pi*L(dim)))^2))+sum(Ufun(L51004));
end
if Benchmark_Function_ID==14
aS=[-32 -16 0 16 32 -32 -16 0 16 32 -32 -16 0 16 32 -32 -16 0 16 32 -32 -16 0 16 32;...
-32 -32 -32 -32 -32 -16 -16 -16 -16 -16 0 0 0 0 0 16 16 16 16 16 32 32 32 32 32];
for j=1:25
bS(j)=sum((L‘-aS(:j)).^6);
end
fit=(1/500+sum(1./([1:25]+bS))).^(-1);
end
if Benchmark_Function_ID==15
aK=[.1957 .1947 .1735 .16 .0844 .0627 .0456 .0342 .0323 .0235 .0246];
bK=[.25 .5 1 2 4 6 8 10 12 14 16];bK=1./bK;
fit=sum((aK-((L(1).*(bK.^2+L(2).*bK))./(bK.^2+L(3).*bK+L(4)))).^2);
end
if Benchmark_Function_ID==16
fit=4*(L(1)^2)-2.1*(L(1)^4)+(L(1)^6)/3+L(1)*L(2)-4*(L(2)^2)+4*(L(2)^4);
end
if Benchmark_Function_ID==17
fit=(L(2)-(L(1)^2)*5.1/(4*(pi^2))+5/pi*L(1)-6)^2+10*(1-1/(8*pi))*cos(L(1))+10;
end
if Benchmark_Function_ID==18
fit=(1+(L(1)+L(2)+1)^2*(19-14*L(1)+3*(L(1)^2)-14*L(2)+6*L(1)*L(2)+3*L(2)^2))*...
(30+(2*L(1)-3*L(2))^2*(18-32*L(1)+12*(L(1)^2)+48*L(2)-36*L(1)*L(2)+27*(L(2)^2)));
end
if Benchmark_Function_ID==19
aH=[3 10 30;.1 10 35;3 10 30;.1 10 35];cH=[1 1.2 3 3.2];
pH=[.3689 .117 .2673;.4699 .4387 .747;.1091 .8732 .5547;.03815 .5743 .8828];
fit=0;
for i=1:4
fi
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 1318 2020-11-29 20:15 license.txt
文件 4047 2020-11-29 20:15 PSOGSA_v3\benchmark_functions.m
文件 2128 2020-11-29 20:15 PSOGSA_v3\benchmark_functions_details.m
文件 1339 2020-11-29 20:15 PSOGSA_v3\license.txt
文件 845 2020-11-29 20:15 PSOGSA_v3\Main.m
文件 164559 2020-11-29 20:15 PSOGSA_v3\PSOGSA.jpg
文件 5736 2020-11-29 20:15 PSOGSA_v3\PSOGSA.m
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