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+// Example with objective function, equality, inequality constraints and variable bounds
+
+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];
+Aeq = [1,3]
+beq= [5]
+lb = [0 0]
+ub = [2 1.5]
+
+//Output
+//Optimal Solution Found.
+// hessian =
+//
+// 2. 0.
+// 0. 2.
+// gradient =
+//
+// 0.9999999 3.
+// lambda =
+//
+// lower: [1.820D-08,6.060D-09]
+// upper: [6.059D-09,0.7267088]
+// ineqlin: [0.3633544,7.251D-08,3.030D-09,3.463D-09,9.093D-09,9.096D-09]
+// eqlin: -1.3633544
+// ineqnonlin: [0x0 constant]
+// eqnonlin: [0x0 constant]
+// output =
+//
+// Iterations: 21
+// Cpu_Time: 0.2
+// Objective_Evaluation: 26
+// Dual_Infeasibility: 9.075D-11
+// exitflag =
+//
+// 0
+// fopt =
+//
+// 2.5
+// xopt =
+//
+// 0.5000000
+// 1.5
+
+[xopt,fopt,exitflag,output,lambda,gradient,hessian] = fmincon (fun, x0, A, b, Aeq, beq, lb, ub)