Генетический алгоритм: теория и практика. Бураков М.В. - 127 стр.

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СПб ГУАП | Санкт-Петербург

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

function s = test10(x)
s = 8*x(1)+9*x(2)+1�*x(�)
end


A ≤ b A
eq
≤b
eq

>> A = A = [-1 -6 -20; -� -� -1; -1 -1 -1];
>> B = [-90; -70; -25];
>> Lb = [0; 0; 0];

>> [x fval reason] = ga(@test10,�,A,B,[],[],Lb,[])

x =
1�.8176 10.4899 0.6945
fval =
21�.9784
reason =
Optimization terminated:
average change in the fitness value less than options.


Вариант 3


 
 


f
= − + −
+ − + ≤
− ≤
≤ ≤
≤ ≤

function s = test20(x)
s = 100*(x(1)^2–x(2))^2+(1-x(1))^2
end


function [c, ceq] = nlc(x)
c = [x(1)*x(2) + x(1) - x(2)+1.5; 10 -x(1)*x(2)];
ceq = [];

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