Quadratic Optimization over a Second-Order Cone with Linear Equality Constraints

Second Order Cone Programming Relaxation of Nonconvex Quadratic Optimization Problems

A disadvantage of the SDP (semidefinite programming) relaxation method for quadratic and/or combinatorial optimization problems lies in its expensive computational cost. This paper proposes a SOCP (second-order-cone programming) relaxation method, which strengthens the lift-and-project LP (linear programming) relaxation method by adding convex quadratic valid inequalities for the positive semid...

Solving A Fractional Program with Second Order Cone Constraint

We consider a fractional program with both linear and quadratic equation in numerator and denominator  having second order cone (SOC) constraints. With a suitable change of variable, we transform the problem into a  second order cone programming (SOCP)  problem.  For the quadratic fractional case, using a relaxation, the problem is reduced to a semi-definite optimization (SDO) program. The p...

Quadratic third-order tensor optimization problem with quadratic constraints

Quadratically constrained quadratic programs (QQPs) problems play an important modeling role in many diverse problems. These problems are in general NP hard and numerically intractable. Semidefinite programming (SDP) relaxations often provide good approximate solutions to these hard problems. For several special cases of QQP, e.g., convex programs and trust region subproblems, SDP relaxation pr...

A Smoothing SQP Method for Mathematical Programs with Linear Second-Order Cone Complementarity Constraints∗

In this paper, we focus on the mathematical program with second-order cone (SOC) complementarity constraints, which contains the well-known mathematical program with nonnegative complementarity constraints as a subclass. For solving such a problem, we propose a smoothing-based sequential quadratic programming (SQP) methods. We first replace the SOC complementarity constraints with equality cons...

Computational Experiments With a Linear Approximation of Second-Order Cone Optimization