The PDHG algorithm provides a new capability for solving difficult linear programming (LP) problems: the ability to find low-accuracy solutions quickly. While such solutions may not be applicable in a...

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This paper takes an empirical look at asymptotic runtime growth rates for the most widely used algorithms for solving linear programming (LP) problems across a set of six optimization application area...

Recent enhancements to the Primal-Dual Hybrid Gradient (PDHG) algorithm have enabled GPUs to efficiently solve large linear programming problems, often faster than the long-dominant simplex and ...

First-order methods based on the PDHG algorithm have recently emerged as a viable option for efficiently solving large-scale linear programming problems. One highly desirable property of these methods...

At the Gurobi Summit in Vienna, a solver tuning challenge turned into a race for performance—and a Sachertorte. Here’s how smart parameter choices won me cake and deeper lessons in optimization.

At Gurobi Optimization, we're on a mission! A mission that focuses on mathematical optimization. We empower our customers to expand their use of mathematical optimization technology to make smarter de...