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// Example with objective function and inequality constraints
function y=fun(x)
y=x(1)*x(1)+x(2)*x(2);
endfunction
x0 = [1,2];
A=[1,1 ; 1,1/4 ; 1,-1 ; -1/4,-1 ; -1,-1 ; -1,1];
b=[2;1;2;1;-1;2];
//Output
//Optimal Solution Found.
// hessian =
//
// 2. - 7.451D-09
// - 7.451D-09 2.
// gradient =
//
// 1.0000000 1.
// lambda =
//
// lower: [0,0]
// upper: [0,0]
// ineqlin: [9.087D-09,2.424D-08,4.546D-09,5.596D-09,1,4.544D-09]
// eqlin: [0x0 constant]
// ineqnonlin: [0x0 constant]
// eqnonlin: [0x0 constant]
// output =
//
// Iterations: 8
// Cpu_Time: 0.112
// Objective_Evaluation: 9
// Dual_Infeasibility: 1.299D-11
// exitflag =
//
// 0
// fopt =
//
// 0.5
// x0pt =
//
// 0.5000000
// 0.5000000
[x0pt,fopt,exitflag,gradient,hessian] = intfmincon(f,x0,intcon, A, b)
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