2 %> \f[\min f(x)=x_1+x_2\f] subject to \f[x_1^2+(x_2-1)^2-1=0 \f]
3 %> @author <a href="http://people.epfl.ch/michel.bierlaire">Michel Bierlaire</a>
4 %> @date Thu Mar 26 13:43:46 2015
8 %> @param x value of the variables
9 %> @param index If 0, the objective
function is evaluated. If not, the constraint number index is evaluated.
10 %> @
return f value of the
function 11 %> @
return g value of the gradient
12 %> @
return H value of the hessian
13 function [f,g,H] =
ex2002(x,index)
21 f = x(1) * x(1) + (x(2)-1.0) * (x(2)-1.0) - 1.0 ;
22 g = [ 2 * x(1) ; 2 * (x(2)-1) ] ;
26 error(
"There is only one constraint") ;
function ex2002(in x, in index)