''Conversion to function_handle from double is not possible.''
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I get this error when I run my code. I was looking up what this error means, but I can't figure it out in context of my code.. This is main code.
clc
clear all
global x1e x2e x3e x1r x2r x3r alfa12 alfa13 alfa23
%LLE podatci - ekstrakcija aromata smjesom TTEG i vode - 6 komponenata (heptan) na 60°C
%eksperimentalni podatci - ekstrakt
x1e = [0.0140 0.0175 0.0163 0.0188 0.0181 0.0227 0.0228 0.0214 0.0191 0.0208];
x2e = [0.0729 0.0696 0.106 0.1041 0.1107 0.0931 0.0732 0.0739 0.113 0.069];
x3e = 1 - x1e - x2e;
%eksperimentalni podatci - rafinat
x1r = [0.689 0.6289 0.485 0.4727 0.4332 0.6831 0.6967 0.6553 0.4507 0.6139];
x2r = [0.275 0.2855 0.4418 0.3501 0.4056 0.313 0.2716 0.271 0.4436 0.253];
x3r = 1 - x1r - x2r;
%Optimizacija NRTL parametara - Metoda Sorensena i Arlta
%1. stupanj optimizacije - opis fazne ravnoteze - geneticki algoritam
%parametri neslucajnosti
alfa12 = 0.3;
alfa13 = 0.3;
alfa23 = 0.2;
rng default
%poziv funkcije cilja
OF_A = @OF_2_6H_60C;
%definiranje strukture problema
problem.fitnessfcn = OF_A;
problem.nvars = 6;
problem.options = optimoptions('ga');
[x,fval] = ga(problem)
This is function I called in main code.
function [OF2] = OF_2_6H_60C(tau12,tau13,tau21,tau23,tau31,tau32)
global x1e x2e x3e x1r x2r x3r alfa12 alfa13 alfa23
syms tau12 tau13 tau21 tau23 tau31 tau32
G12 = exp(-alfa12*tau12);
G13 = exp(-alfa13*tau13);
G21 = exp(-alfa12*tau21);
G23 = exp(-alfa23*tau23);
G31 = exp(-alfa13*tau31);
G32 = exp(-alfa23*tau32);
A1e = (x2e.*tau21*G21 + x3e.*tau31*G31)./(x1e + x2e.*G21 + x3e.*G31) + (((x1e./(x1e + x2e.*G21 + x3e.*G31)).*(-(x2e.*tau21*G21 + x3e.*tau31*G31)./(x1e + x2e.*G21 + x3e.*G31))) + ((x2e.*G12)./(x1e.*G12 + x2e + x3e.*G32)).*(tau21 - (x1e.*tau12*G12 + x3e.*tau32*G32)./(x1e.*G12 + x2e + x3e.*G32))) + ((x3e.*G13./(x1e.*G13 + x2e.*G23 + x3e)).*(tau31 - (x1e.*tau13*G13 + x2e.*tau23*G23)./(x1e.*G13 + x2e.*G23 + x3e)));
gamma1e = exp(A1e);
A2e = (x1e.*tau12*G12 + x3e.*tau32*G32)./(x1e.*G12 + x2e + x3e.*G32) + ((x1e.*G21./(x1e + x2e.*G21 + x3e.*G31)).*(tau12 - (x2e.*tau21*G21 + x3e.*tau31*G31)./(x1e + x2e.*G21 + x3e.*G31))) + ((x2e./(x1e.*G12 + x2e + x3e.*G32)).*(-(x1e.*tau12*G12 + x3e.*tau32*G32)./(x1e.*G12 + x2e + x3e.*G32))) + ((x3e.*G23./(x1e.*G13 + x2e.*G23 + x3e)).*(tau32 - (x1e.*tau13*G13 + x2e.*tau23*G23)./(x1e.*G13 + x2e.*G23 + x3e)));
gamma2e = exp(A2e);
A3e = (x1e.*tau13*G13 + x2e.*tau23*G23)./(x1e.*G13 + x2e.*G23 + x3e) + ((x1e.*G21./(x1e + x2e.*G21 + x3e.*G31)).*(tau13 - (x2e.*tau21*G21 + x3e.*tau31*G31)./(x1e + x2e.*G21 + x3e.*G31))) + ((x2e.*G32./(x1e.*G12 + x2e + x3e.*G32)).*(tau23 - (x1e.*tau12*G12)./(x1e.*G12 + x2e + x3e.*G32))) + ((x3e./(x1e.*G13 + x2e.*G23 + x3e)).*(-(x1e.*tau13*G13 + x2e.*tau23*G23)./(x1e.*G13 + x2e.*G23 + x3e)));
gamma3e = exp(A3e);
A1r = (x2r.*tau21*G21 + x3r.*tau31*G31)./(x1r + x2r.*G21 + x3r.*G31) + ((x1r./(x1r + x2r.*G21 + x3r.*G31)).*(-(x2r.*tau21*G21 + x3e.*tau31*G31)./(x1r + x2r.*G21 + x3r.*G31))) + ((x2r.*G12)./(x1r.*G12 + x2r + x3e.*G32)).*(tau21 - ((x1r.*tau12*G12 + x3r.*tau32*G32)./(x1r.*G12 + x2r + x3r.*G32))) + ((x3r.*G13./(x1r.*G13 + x3r)).*(tau31 - (x1r.*tau13*G13 + x2r.*tau23*G23)./(x1r.*G13 + x2r.*G23 + x3r)));
gamma1r = exp(A1r);
A2r = (x1r.*tau12*G12 + x3r.*tau32*G32)./(x1r.*G12 + x2r + x3r.*G32) + ((x1r.*G21./(x1r + x2r.*G21 + x3r.*G32)).*(tau12 - (x2r.*tau21.*G21 + x3r.*tau31*G31)./(x1r + x2r.*G21 + x3r.*G31))) + ((x2r./(x1r.*G12 + x2r + x3r.*G32)).*(-(x1r.*tau12*G12 + x3r.*tau32*G32)./(x1r.*G12 + x2r + x3r.*G32))) + ((x3r.*G23./(x1r.*G13 + x2r.*G23 + x3r)).*(tau32 - (x1r.*tau13*G13 + x2r.*tau23*G23 + x3r)));
gamma2r = exp(A2r);
A3r = (x1r.*tau13*G13 + x2r.*tau23*G23)./(x1r.*G13 + x2r.*G23 + x3r) + ((x1r.*G31./(x1r + x2r.*G21 + x3r.*G31)).*(tau13 - (x2r.*tau21*G21 + x3r.*tau31*G31)./(x1r + x2r.*G21 + x3r.*G31))) + ((x2r.*G32./(x1r.*G12 + x2r + x3r.*G32)).*(tau23 - (x1r.*tau12*G12)./(x1r.*G12 + x2r + x3r.*G32))) + ((x3r./(x1r.*G13 + x2r.*G23 + x3r)).*(-(x1r.*tau13*G13 + x2r.*tau23*G23)./(x1r.*G13 + x2r.*G23 + x3r)));
gamma3r = exp(A3r);
for i = 1:10
A(i)=((x1e(i)*gamma1e(i) - x1r(i)*gamma1r(i))/(x1e(i)*gamma1e(i) + x1r(i)*gamma1r(i))^2) + ((x2e(i)*gamma2e(i) - x2r(i)*gamma2r(i))/(x2e(i)*gamma2e(i) + x2r(i)*gamma2r(i))^2) + ((x3e(i)*gamma3e(i) - x3r(i)*gamma3r(i))/(x3e(i)*gamma3e(i) + x3r(i).*gamma3r(i))^2);
end
F2 = sum(A,'all');
OF2 = matlabFunction(F2)
end
5 Comments
According to the ga documentation "Write the objective function to accept a row vector of length nvars and return a scalar value." Instead of returning a numeric value as the documentation requires your function returns a function handle (i.e. that returned by matlabFunction). I would not expect that to work.
Dario Miric
on 25 Jan 2022
ga hands numerical test values to OF_A and tries to improve them in the course of the optimization.
So remove the line
syms tau12 tau13 ...
in OF_A and simply set
OF2 = F2
at the end.
And define
OF_A = @{x) OF_2_6H_60C(x(1),x(2),x(3),x(4),x(5),x(6))
instead of your setting.
Dario Miric
on 25 Jan 2022
Edited: Dario Miric
on 25 Jan 2022
Torsten
on 26 Jan 2022
In function OF_2_6H_60C, you can work with the name tau for the variables.
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