[Ipopt-tickets] [Ipopt] #193: Quadratic constraint LP using Ipopt

[Ipopt]

#193: Quadratic constraint LP using Ipopt
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Reporter:  pravinbs       |      Owner:  ipopt-team
    Type:  clarification  |     Status:  new
Priority:  normal         |  Component:  Ipopt
 Version:  3.9            |   Severity:  normal
Keywords:  QCLP, Convex   |
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 I am unable to solve the following using Ipopt. Objective is to minimize
 transaction costs with an upper bound on the variance of basket of stocks.
 Ipopt either says Infeasible or exceeds maximum iterations. Is there any
 particular reason or is it just my implementation that is wrong? I am able
 to solve the same problem using Gurobi solver. I am new to Ipopt and would
 appreciate any directions you could provide.

 min C^T^X

 s.t.

 0 <= X^T^ΣX <= gU

 0 <= SUM(X(i)) <= 0

 -1 <= X(i) <= 1

 where

 C is the vector of transaction costs (all positive)

 X is vector of active weights

 Σ is the positive definite covariance matrix

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Ticket URL: <https://projects.coin-or.org/ticket/193>
Ipopt <http://projects.coin-or.org/Ipopt>
Interior-point optimizer for nonlinear programs.