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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
+// xopt =
+//
+// 0.5000000
+// 0.5000000
+
+[xopt,fopt,exitflag,output,lambda,gradient,hessian] = fmincon (fun, x0, A, b)