19 citations · 21 across the 9 of their papers we have counts for
7 papers · 1 filter
A quantum dual logarithmic barrier method for linear optimization
Zeguan Wu, Pouya Sampourmahani, Mohammadhossein Mohammadisiahroudi +1
Quantum computing has the potential to speed up some optimization methods. One can use quantum computers to solve linear systems via Quantum Linear System Algorithms (QLSAs). QLSAs…
A preconditioned inexact infeasible quantum interior point method for linear optimization
Zeguan Wu, Xiu Yang, Tamás Terlaky
Quantum Interior Point Methods (QIPMs) have been attracting significant interests recently due to their potential of solving optimization problems substantially faster than state-o…
Improvements to Quantum Interior Point Method for Linear Optimization
Mohammadhossein Mohammadisiahroudi, Zeguan Wu, Brandon Augustino +2
Quantum linear system algorithms (QLSA) have the potential to speed up Interior Point Methods (IPM). However, a major challenge is that QLSAs are inexact and sensitive to the condi…
On relaxations of the max -cut problem formulations
Ramin Fakhimi, Hamidreza Validi, Illya V. Hicks +2
A tight continuous relaxation is a crucial factor in solving mixed integer formulations of many NP-hard combinatorial optimization problems. The (weighted) max -cut problem is a…
Generating Linear, Semidefinite, and Second-order Cone Optimization Problems for Numerical Experiments
Mohammadhossein Mohammadisiahroudi, Ramin Fakhimi, Brandon Augustino +1
The numerical performance of algorithms can be studied using test sets or procedures that generate such problems. This paper proposes various methods for generating linear, semidef…
On Semidefinite Representations of Second-order Conic Optimization Problems
Pouya Sampourmahani, Mohammadhossein Mohammadisiahroudi, Tamás Terlaky
Second-order conic optimization (SOCO) can be considered as a special case of semidefinite optimization (SDO). In the literature it has been advised that a SOCO problem can be embe…