Genetic algorithm problem in matrix index

Dear sir

i have problem with this code . can any one help me and thanks advance

error

Index exceeds matrix dimensions.

Error in Untitled3 (line 47)

CTI1 = A(1,1)*x(1)+A(1,6)*x(6)

the code

%To minimize our fitness function using the ga function, we need to pass in a function handle to the fitness function as well as specifying the number of variables as the second argument. Lower and upper bounds are provided as LB and UB respectively. In addition, we also need to pass in a function handle to the nonlinear constraint function.
tic
clear 
clc
ObjectiveFunction = @simple_fitness;
nvars = 14;                                                     % Number of variables
LB = [0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05]; % Lower bound for (x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14)
UB = [1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 ]; % Upper bound for (x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14)
 A=zeros(20,14); b=zeros(20,1);
 A(1,1)=+2.174;     A(1,6)=-1.777;   b(1)=-0.3;  %first row
 A(2,1)=-3.555;    A(2,2)=+1.159;    b(2)=-0.3;  %second row
 A(3,2)=+1.159;     A(3,7)=-2.137;   b(3)=-0.3;  %third row
 A(4,2)=-1.272;    A(4,3)=+2.880;    b(4)=-0.3;  %fourth row
 A(5,3)=-3.593;    A(5,4)=+3.043;    b(5)=-0.3;  %fifth row
 A(6,4)=-3.818;    A(6,5)=+1.402;    b(6)=-0.3;  %sixth row
 A(7,5)=-1.650;    A(7,6)=+1.519;    b(7)=-0.3;  %seventh row
 A(8,5)=-1.650;    A(8,7)=+1.606;    b(8)=-0.3;  %eighth row
 A(9,6)=+1.519;     A(9,14)=-2.143;  b(9)=-0.3;  %nighth row
 A(10,7)=+1.606;    A(10,13)=-2.629; b(10)=-0.3; %tenth row
 A(11,7)=-2.137;   A(11,8)=+1.806;   b(11)=-0.3; %eleventh row
 A(12,8)=+1.806;    A(12,9)=-1.622;  b(12)=-0.3; %tweleventh row
 A(13,9)=+1.948;    A(13,10)=-3.605; b(13)=-0.3; %thirteenth row
 A(14,10)=+2.753;   A(14,11)=-3.935; b(14)=-0.3; %fourteenth row
 A(15,11)=+3.105;   A(15,12)=-1.287; b(15)=-0.3; %fiveteenth row
 A(16,12)=+1.181;   A(16,13)=-2.629; b(16)=-0.3; %sixteenth row
 A(17,12)=+1.181;   A(17,14)=-2.143; b(17)=-0.3; %seventennth row
 A(18,8)=-2.232;   A(18,13)=+1.816;  b(18)=-0.3; %eighteenth row
 A(19,1)=-3.555;   A(19,14)=+1.608;  b(19)=-0.3; %nighnteenth row
 A(20,9)=-1.622;   A(20,14)=+1.608;  b(20)=-0.3; %twinty row
Aeq=[];
beq=[];
nonlcon=[];
IntCon=[];
rng default % For reproducibility
options=gaoptimset('plotfcns',{'gaplotgenealogy','gaplotselection', 'gaplotbestf' ,@gaplotscorediversity});
options= gaoptimset(options,'Tolfun',1e-6,'TolCon',1e-3,'stallGenlimit',50);
options= gaoptimset(options,'MutationFcn',{@mutationadaptfeasible});
options=gaoptimset(options,'PopulationSize',200);
options=gaoptimset(options,'PopulationType','doubleVector');
options=gaoptimset(options,'CrossoverFcn',{@crossoverarithmetic});
options=gaoptimset(options,'Display', 'iter');
[x,fval,exitflag,output,population,scores] = ga(ObjectiveFunction,nvars,A,b,Aeq,beq,LB,UB,nonlcon,IntCon,options)
toc
CTI1 = A(1,1)*x(1)+A(1,6)*x(6)
CTI2 = A(2,1)*x(1)+ A(2,2)*x(2)
CTI3 = A(3,2)*x(2)+ A(3,7)*x(7)
CTI4 = A(4,2)*x(2)+ A(4,3)*x(3)
CTI5 = A(5,3)*x(3)+ A(5,4)*x(4)
CTI6 = A(6,4)*x(4)+ A(6,5)*x(5)
CTI7 = A(7,5)*x(5)+ A(7,6)*x(6)
CTI8 = A(8,5)*x(5)+ A(8,7)*x(7)
CTI9 = A(9,6)*x(6)+ A(9,14)*x(14)
CT10 = A(10,7)*x(7)+ A(10,13)*x(13)
CTI11= A(11,7)*x(7)+ A(11,8)*x(8)
CTI12= A(12,8)*x(8)+ A(12,9)*x(9)
CTI13= A(13,9)*x(9)+ A(13,10)*x(10)
CTI14= A(14,10)*x(10)+ A(14,11)*x(11)
CTI15= A(15,11)*x(11)+ A(15,12)*x(12)
CTI16= A(16,12)*x(12)+ A(16,13)*x(13)
CTI17= A(17,12)*x(12)+ A(17,14)*x(14)
CTI18= A(18,8)*x(8)+ A(18,13)*x(13)
CTI19= A(19,1)*x(1)+ A(19,14)*x(14)
CTI20= A(20,9)*x(9)+ A(20,14)*x(14) 

Answer 1

[Stephan]

Hi,

you are using the simple_fitness function, which is an implementation of the Rosenbrock function. This function is a built in example function and has a number of variables = 2. How do you expect your code to run on 14 variables with this function?

Maybe you did write your own fitness function, which is accidently named like the built in one. If so, rename the .m-file you created and provide the function together with the other code if there are still more issues.

Best regards

Stephan

[tahseen alshmary]

my function is

function y = simple_fitness(x)

y = 2.174*x(1)+1.159*x(2)+2.880*x(3)+3.043*x(4)+1.402*x(5)+1.519*x(6)+1.606*x(7)+1.806*x(8)+1.363*x(9)+2.753*x(10)+3.105*x(11)+1.181*x(12)+1.816*x(13)+1.608*x(14);

end

[Stephan]

This is a linear objective function with linear constraints - use linprog (and rename your objective function)

[tahseen alshmary]

hi stephan

i know its linear objective function , but i need solve it with genetic algorithm .

previously i solve one same equation but different in constrain value . it is work normally

[Stephan]

Hi,

your function does not have a feasible solution under the given conditions - i checked this with linprog:

lb = 0.05*ones(1,14); % Lower bound for (x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14)
ub = 1.1*ones(1,14); % Upper bound for (x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14)
A=zeros(20,14); b=zeros(20,1);
A(1,1)=+2.174;     A(1,6)=-1.777;   b(1)=-0.3;  %first row
A(2,1)=-3.555;    A(2,2)=+1.159;    b(2)=-0.3;  %second row
A(3,2)=+1.159;     A(3,7)=-2.137;   b(3)=-0.3;  %third row
A(4,2)=-1.272;    A(4,3)=+2.880;    b(4)=-0.3;  %fourth row
A(5,3)=-3.593;    A(5,4)=+3.043;    b(5)=-0.3;  %fifth row
A(6,4)=-3.818;    A(6,5)=+1.402;    b(6)=-0.3;  %sixth row
A(7,5)=-1.650;    A(7,6)=+1.519;    b(7)=-0.3;  %seventh row
A(8,5)=-1.650;    A(8,7)=+1.606;    b(8)=-0.3;  %eighth row
A(9,6)=+1.519;     A(9,14)=-2.143;  b(9)=-0.3;  %nighth row
A(10,7)=+1.606;    A(10,13)=-2.629; b(10)=-0.3; %tenth row
A(11,7)=-2.137;   A(11,8)=+1.806;   b(11)=-0.3; %eleventh row
A(12,8)=+1.806;    A(12,9)=-1.622;  b(12)=-0.3; %tweleventh row
A(13,9)=+1.948;    A(13,10)=-3.605; b(13)=-0.3; %thirteenth row
A(14,10)=+2.753;   A(14,11)=-3.935; b(14)=-0.3; %fourteenth row
A(15,11)=+3.105;   A(15,12)=-1.287; b(15)=-0.3; %fiveteenth row
A(16,12)=+1.181;   A(16,13)=-2.629; b(16)=-0.3; %sixteenth row
A(17,12)=+1.181;   A(17,14)=-2.143; b(17)=-0.3; %seventennth row
A(18,8)=-2.232;   A(18,13)=+1.816;  b(18)=-0.3; %eighteenth row
A(19,1)=-3.555;   A(19,14)=+1.608;  b(19)=-0.3; %nighnteenth row
A(20,9)=-1.622;   A(20,14)=+1.608;  b(20)=-0.3; %twinty row
Aeq=[];
beq=[];
f = [2.174 1.159 2.880 3.043 1.402 1.519 1.606 1.806 1.363 2.753 3.105 1.181 1.816 1.608];
[x,fval,exitflag,output,lambda] = linprog(@fitness,A,b,Aeq,beq,lb,ub)

Result is:

>> test
No feasible solution found.

Linprog stopped because no point satisfies the constraints.

x =

     []


fval =

     []


exitflag =

    -2


output = 

  struct with fields:

         iterations: 0
            message: 'No feasible solution found.↵↵Linprog stopped because no point satisfies the constraints.'
          algorithm: 'dual-simplex'
    constrviolation: []
      firstorderopt: []


lambda =

     []

So you can use every solver you want - either there is an issue in your constraints, your bounds or in your objective function - one thing is for sure: there is no solution to this problem in the given form . So if you fix the problem (whatever it is), i think also ga should find some (nearly) optimal solution. Since ga doesnt find anything useful you get an empty x and in the result you get the error you have, because you reference to an empty x, which causes an error.

Thats it.

[tahseen alshmary]

okay thanks

do you know how can i solve this problem

[Stephan]

Set the upper bounds to:

ub = 2*ones(1,14);

linprog finds an optimal solution under this conditions , so ga should also find a good solution.

With solving this problem, you have a running code without error messages.

If this was helpful for you, please make sure to accept my answer.

[tahseen alshmary]

yes thank you very much

but the best fuction (total value very high )=22.054

must be less than 10

but i have another idea make nonlinear constraint fuction will find solution

many ,many thanks for you

[Stephan]

i wish you success, please accept useful answers.

[tahseen alshmary]

thanks you so much