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【智能优化算法-黑猩猩算法】基于增强型黑猩猩优化器算法求解单目标优化问题附matlab代码

發布時間：2023/12/20 循环神经网络 50 豆豆

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1 內容介紹

This article proposes a novel metaheuristic algorithm called Chimp Optimization Algorithm (ChOA) inspired by the individual intelligence and sexual motivation of chimps in their group hunting, which is different from the other social predators. ChOA is designed to further alleviate the two problems of slow convergence speed and trapping in local optima in solving high-dimensional problems. In this article, a mathematical model of diverse intelligence and sexual motivation is proposed. Four types of chimps entitled attacker, barrier, chaser, and driver are employed for simulating the diverse intelligence. Moreover, the four main steps of hunting, driving, blocking, and attacking, are implemented. Afterward, the algorithm is tested on 30 well-known benchmark functions, and the results are compared to four newly proposed meta-heuristic algorithms in term of convergence speed, the probability of getting stuck in local minimums, and the accuracy of obtained results. The results indicate that the ChOA outperforms the other benchmark optimization algorithms.

2 仿真代碼

%___________________________________________________________________%
% ?Dimension Learning Based Chimp Optimizer for Solving Engineering ? ? ? ? ?%
% ?Problems (I-ChoA) source codes version 1.0 ? ? ? ? ? ? ? ? ? ? ? ?%
% ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? %
% ?Developed in MATLAB R2018a ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? %
% ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? %
% ?Author and programmer: Dr. Narinder Singh, Department of Mathematics,?
?% Punjabi University, Patiala, Punjab, INDIA ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?%
% ?e-Mail:narindersinghgoria@gmail.com ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? %
% ResearchGate:https://www.researchgate.net/profile/Dr-Narinder-Singh?
% Google Scholar:
% https://scholar.google.co.in/citations?user=ypebIpIAAAAJ&hl=en?
%___________________________________________________________________%
%++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ %

% You can simply define your cost in a seperate file and load its handle to fobj?
% The initial parameters that you need are:
%__________________________________________
% fobj = @YourCostFunction
% dim = number of your variables
% Max_iteration = maximum number of generations
% N = number of search agents
% lb=[lb1,lb2,...,lbn] where lbn is the lower bound of variable n
% ub=[ub1,ub2,...,ubn] where ubn is the upper bound of variable n
% If all the variables have equal lower bound you can just
% define lb and ub as two single number numbers
%##########################################################################
%##########################################################################

function [lb,ub,dim,fobj] = Get_Functions_details(F)

switch F
? ? case 'F1'
? ? ? ? fobj = @F1;
? ? ? ? lb=-100;
? ? ? ? ub=100;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F2'
? ? ? ? fobj = @F2;
? ? ? ? lb=-10;
? ? ? ? ub=10;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F3'
? ? ? ? fobj = @F3;
? ? ? ? lb=-100;
? ? ? ? ub=100;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F4'
? ? ? ? fobj = @F4;
? ? ? ? lb=-100;
? ? ? ? ub=100;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F5'
? ? ? ? fobj = @F5;
? ? ? ? lb=-30;
? ? ? ? ub=30;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F6'
? ? ? ? fobj = @F6;
? ? ? ? lb=-100;
? ? ? ? ub=100;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F7'
? ? ? ? fobj = @F7;
? ? ? ? lb=-1.28;
? ? ? ? ub=1.28;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F8'
? ? ? ? fobj = @F8;
? ? ? ? lb=-500;
? ? ? ? ub=500;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F9'
? ? ? ? fobj = @F9;
? ? ? ? lb=-5.12;
? ? ? ? ub=5.12;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F10'
? ? ? ? fobj = @F10;
? ? ? ? lb=-32;
? ? ? ? ub=32;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F11'
? ? ? ? fobj = @F11;
? ? ? ? lb=-600;
? ? ? ? ub=600;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F12'
? ? ? ? fobj = @F12;
? ? ? ? lb=-50;
? ? ? ? ub=50;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F13'
? ? ? ? fobj = @F13;
? ? ? ? lb=-50;
? ? ? ? ub=50;
? ? ? ? dim=30;
? ? ? ??
? ? case 'F14'
? ? ? ? fobj = @F14;
? ? ? ? lb=-65.536;
? ? ? ? ub=65.536;
? ? ? ? dim=2;
? ? ? ??
? ? case 'F15'
? ? ? ? fobj = @F15;
? ? ? ? lb=-5;
? ? ? ? ub=5;
? ? ? ? dim=4;
? ? ? ??
? ? case 'F16'
? ? ? ? fobj = @F16;
? ? ? ? lb=-5;
? ? ? ? ub=5;
? ? ? ? dim=2;
? ? ? ??
? ? case 'F17'
? ? ? ? fobj = @F17;
? ? ? ? lb=[-5,0];
? ? ? ? ub=[10,15];
? ? ? ? dim=2;
? ? ? ??
? ? case 'F18'
? ? ? ? fobj = @F18;
? ? ? ? lb=-2;
? ? ? ? ub=2;
? ? ? ? dim=2;
? ? ? ??
? ? case 'F19'
? ? ? ? fobj = @F19;
? ? ? ? lb=0;
? ? ? ? ub=1;
? ? ? ? dim=3;
? ? ? ??
? ? case 'F20'
? ? ? ? fobj = @F20;
? ? ? ? lb=0;
? ? ? ? ub=1;
? ? ? ? dim=6; ? ??
? ? ? ??
? ? case 'F21'
? ? ? ? fobj = @F21;
? ? ? ? lb=0;
? ? ? ? ub=10;
? ? ? ? dim=4; ? ?
? ? ? ??
? ? case 'F22'
? ? ? ? fobj = @F22;
? ? ? ? lb=0;
? ? ? ? ub=10;
? ? ? ? dim=4; ? ?
? ? ? ??
? ? case 'F23'
? ? ? ? fobj = @F23;
? ? ? ? lb=0;
? ? ? ? ub=10;
? ? ? ? dim=4; ? ? ? ? ? ?
end

end

% F1

function o = F1(x)
o=sum(x.^2);
end

% F2

function o = F2(x)
o=sum(abs(x))+prod(abs(x));
end

% F3

function o = F3(x)
dim=size(x,2);
o=0;
for i=1:dim
? ? o=o+sum(x(1:i))^2;
end
end

% F4

function o = F4(x)
o=max(abs(x));
end

% F5

function o = F5(x)
dim=size(x,2);
o=sum(100*(x(2:dim)-(x(1:dim-1).^2)).^2+(x(1:dim-1)-1).^2);
end

% F6

function o = F6(x)
o=sum(abs((x+.5)).^2);
end

% F7

function o = F7(x)
dim=size(x,2);
o=sum([1:dim].*(x.^4))+rand;
end

% F8

function o = F8(x)
o=sum(-x.*sin(sqrt(abs(x))));
end

% F9

function o = F9(x)
dim=size(x,2);
o=sum(x.^2-10*cos(2*pi.*x))+10*dim;
end

% F10

function o = F10(x)
dim=size(x,2);
o=-20*exp(-.2*sqrt(sum(x.^2)/dim))-exp(sum(cos(2*pi.*x))/dim)+20+exp(1);
end

% F11

function o = F11(x)
dim=size(x,2);
o=sum(x.^2)/4000-prod(cos(x./sqrt([1:dim])))+1;
end

% F12

function o = F12(x)
dim=size(x,2);
o=(pi/dim)*(10*((sin(pi*(1+(x(1)+1)/4)))^2)+sum((((x(1:dim-1)+1)./4).^2).*...
(1+10.*((sin(pi.*(1+(x(2:dim)+1)./4)))).^2))+((x(dim)+1)/4)^2)+sum(Ufun(x,10,100,4));
end

% F13

function o = F13(x)
dim=size(x,2);
o=.1*((sin(3*pi*x(1)))^2+sum((x(1:dim-1)-1).^2.*(1+(sin(3.*pi.*x(2:dim))).^2))+...
((x(dim)-1)^2)*(1+(sin(2*pi*x(dim)))^2))+sum(Ufun(x,5,100,4));
end

% F14

function o = F14(x)
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((x'-aS(:,j)).^6);
end
o=(1/500+sum(1./([1:25]+bS))).^(-1);
end

% F15

function o = F15(x)
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;
o=sum((aK-((x(1).*(bK.^2+x(2).*bK))./(bK.^2+x(3).*bK+x(4)))).^2);
end

% F16

function o = F16(x)
o=4*(x(1)^2)-2.1*(x(1)^4)+(x(1)^6)/3+x(1)*x(2)-4*(x(2)^2)+4*(x(2)^4);
end

% F17

function o = F17(x)
o=(x(2)-(x(1)^2)*5.1/(4*(pi^2))+5/pi*x(1)-6)^2+10*(1-1/(8*pi))*cos(x(1))+10;
end

% F18

function o = F18(x)
o=(1+(x(1)+x(2)+1)^2*(19-14*x(1)+3*(x(1)^2)-14*x(2)+6*x(1)*x(2)+3*x(2)^2))*...
? ? (30+(2*x(1)-3*x(2))^2*(18-32*x(1)+12*(x(1)^2)+48*x(2)-36*x(1)*x(2)+27*(x(2)^2)));
end

% F19

function o = F19(x)
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];
o=0;
for i=1:4
? ? o=o-cH(i)*exp(-(sum(aH(i,:).*((x-pH(i,:)).^2))));
end
end

% F20

function o = F20(x)
aH=[10 3 17 3.5 1.7 8;.05 10 17 .1 8 14;3 3.5 1.7 10 17 8;17 8 .05 10 .1 14];
cH=[1 1.2 3 3.2];
pH=[.1312 .1696 .5569 .0124 .8283 .5886;.2329 .4135 .8307 .3736 .1004 .9991;...
.2348 .1415 .3522 .2883 .3047 .6650;.4047 .8828 .8732 .5743 .1091 .0381];
o=0;
for i=1:4
? ? o=o-cH(i)*exp(-(sum(aH(i,:).*((x-pH(i,:)).^2))));
end
end

% F21

function o = F21(x)
aSH=[4 4 4 4;1 1 1 1;8 8 8 8;6 6 6 6;3 7 3 7;2 9 2 9;5 5 3 3;8 1 8 1;6 2 6 2;7 3.6 7 3.6];
cSH=[.1 .2 .2 .4 .4 .6 .3 .7 .5 .5];

o=0;
for i=1:5
? ? o=o-((x-aSH(i,:))*(x-aSH(i,:))'+cSH(i))^(-1);
end
end

% F22

function o = F22(x)
aSH=[4 4 4 4;1 1 1 1;8 8 8 8;6 6 6 6;3 7 3 7;2 9 2 9;5 5 3 3;8 1 8 1;6 2 6 2;7 3.6 7 3.6];
cSH=[.1 .2 .2 .4 .4 .6 .3 .7 .5 .5];

o=0;
for i=1:7
? ? o=o-((x-aSH(i,:))*(x-aSH(i,:))'+cSH(i))^(-1);
end
end

% F23

function o = F23(x)
aSH=[4 4 4 4;1 1 1 1;8 8 8 8;6 6 6 6;3 7 3 7;2 9 2 9;5 5 3 3;8 1 8 1;6 2 6 2;7 3.6 7 3.6];
cSH=[.1 .2 .2 .4 .4 .6 .3 .7 .5 .5];

o=0;
for i=1:10
? ? o=o-((x-aSH(i,:))*(x-aSH(i,:))'+cSH(i))^(-1);
end
end

function o=Ufun(x,a,k,m)
o=k.*((x-a).^m).*(x>a)+k.*((-x-a).^m).*(x<(-a));
end