Plot 3d to find point of intersection?

Hello

I am trying to find the point of intersection of three functions. I have of course tried different things but haven't yet figured it out. Basically what I want is to plot three functions in one plane each to find the intersection point of these three functions. I need it because I am currently working with unconstrained optimization and linear programming regarding the Simplex method. I have found the point of maximum profit but at that point I also need to find the number of each of the three types of products that is produced. I am thinking it can be done by plotting these three functions in one plane each, but I haven't yet been able to figure it out.

Any help is appreciated.

Here is my script:

    %%Opgave 3
  %With M2x1,C2x1 and T2x1 I have been trying to solve each equation for x1.
    M2x1=solve(40*x1+20*x2+10*x3==460,x1)
    %M2x2=solve(40*x1+20*x2+10*x3==460,x2)
    C2x1=solve(x1+4*x2*2*x3==48,x1)
    %C2x2=solve(x1+4*x2*x3==48,x2)
    T2x1=solve(2*x1+3.5*x2+5*x3==60,x1)
  %T2x2=solve(2*x1+3.5*x2+5*x3==60,x2)

%[x1,x2,x3]=solve('x1=40*(23/2 - x3/4 - (23 - x3/2)/2)+20*(23 - x3/2)+10*x3','x1=(48 - 8*(6/x3)*x3)+4*(6/x3)*2*x3','x1=2*(30 - (5*x3)/2 - (7*(120/7 - (10*x3)/7))/4)+3.5*(120/7 - (10*x3)/7)+5*x3')

%[x1,x2,x3]=solve('x1=23/2 - x3/4 - x2/2','x1=48 - 8*x2*x3','30 - (5*x3)/2 - (7*x2)/4')

%[x1,x2]=solve('x1=23/2 - x3/4 - x2/2','x1=48 - 8*x2*x3')

figure(2);
%M2x1 = @(x2,x3) 23/2 - x3/4 - x2/2;
%C2x1 = @(x2,x3) 48 - 8*x2*x3;
%T2x1 = @(x2,x3) 30 - (5*x3)/2 - (7*x2)/4;
%n=ezsurf(M2x1,[-2 25 -2 25]);
hold on;
%v=ezsurf(C2x1,[-2 25 -2 25]);
%b=ezsurf(T2x1,[-2 25 -2 25]);
%legend('Mængde GaAs','CO2-udledning','Produktionstid')
%axis([-2 25 -2 25 -2 25]);

M2x2=23 - x3./2 - 2.*x1;
T2x3=12 - (7.*x2)/10 - (2.*x1)./5;
syms x2 x3
x2=-10:0.1:100;x3=-10:0.1:100;

M2x1=23/2 - x3./4 - x2./2;
C2x1=48 - 8.*x2.*x3;
T2x1=30 - (5.*x3)./2 - (7.*x2)./4;
  plot3([M2x2,C2x1,T2x3])

%Finding maximum profit
  T=[1 -120 -110 -100 0 0 0 0; 0 10 40 20 1 0 0 460; 0 2 1 4 0 1 0 48; 0 5 2 3.5 0 0 1 60]
  [r,c]=size(T);

for i=2:(s-1)

    if T(1,i)<0
       cn=i %
       Koef=T(2:r,c)./T(2:r,cn);
       D=Koef>=0;
       Koef=Koef(D);
       Koefmin=min(Koef);
       rn=find(Koef==Koefmin);
       rn=rn(1)+1

       for  j=1:r
          if j==rn
             %does nothing with pivot row

          else
             mjk=(T(j,cn))./(T(rn,cn));
             T(j,:)=T(j,:)-mjk*T(rn,:)
          end    
       end

     else
        i=i+1;

     end    
  end

z=T(1,c)
hold off

Where T of course is the augmented matrix and z is the optimal profit. x1 = type 1, x2 = type 2 and x3 = type 3.