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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)
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