[Ipopt] Bound on the objective function value

Z. Caner Taskin taskin at ufl.edu
Wed Feb 11 21:22:56 EST 2009

Hi all,

I am using the C++ interface of Ipopt to solve a convex minimization 
problem. Specifically, the objective function is convex and all 
constraints are linear inequalities. I implemented the functions to 
provide first- and second-order derivatives, and Ipopt can usually solve 
my problem instances to optimality. However, sometimes it stops due to 
the limit on the number of iterations, and for such cases I need to 
calculate a lower bound on the objective function value. Since my 
problem is a convex optimization problem, the Lagrangian function should 
provide a strong dual for my problem. I verified that the value of the 
Lagrangian function is equal to the primal objective function value when 
the problem is solved optimally. However, I am having trouble getting 
consistent results for the  instances for which Ipopt stops due to the 
iteration limit (usually with relatively large dual infeasibility). I 
was wondering if anyone has experience obtaining bounds on the objective 
function value for convex problems?

Thanks in advance,


Z. Caner Taskin

PhD Candidate
Department of Industrial and Systems Engineering
University of Florida

303 Weil Hall, P.O. Box 116595,
Gainesville, FL 32611
Phone: (352) 870 1729
Fax: (352) 392 3537
Website: http://www.zekicanertaskin.com 

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