Abstract: Islanded DC microgrids are vulnerable to voltage instability caused by excessive power demand, which can adversely impact downstream consumers and disrupt overall microgrid operation.

Abstract: In this paper, a design framework based on integer linear programming is proposed for optimizing sparse array structures. We resort to binary vectors to formulate the design problem for ...

HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form $$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad \textrm{s.t.}~ \quad L \leq Ax \leq ...

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer ...

ABSTRACT: This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to ...

NVIDIA's cuOpt leverages GPU technology to drastically accelerate linear programming, achieving performance up to 5,000 times faster than traditional CPU-based solutions. The landscape of linear ...

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A next-gen Lagrange-Newton solver for nonconvex constrained optimization. Unifies barrier and SQP methods in a generic way, and implements various globalization flavors (line search/trust region and ...

Efficiently tackling complex optimization problems, ranging from global package routing to power grid management, has been a persistent challenge. Traditional methods, notably mixed-integer linear ...

Inspired by the decomposition in the hybrid quantum-classical optimization algorithm we introduced in arXiv:1902.04215, we propose here a new (fully classical) approach to solving certain non-convex ...