Abstract: In some optimal control problems, complex relationships between states and inputs cannot be easily represented using continuous constraints, necessitating the use of discrete logic instead.

Abstract: We study the problem of determining an effective exploration strategy in static and non-linear optimization problems, which depend on an unknown scalar parameter to be learned from online ...

NVIDIA's GPU-accelerated cuOpt engine discovers new solutions for four MIPLIB benchmark problems, outperforming CPU solvers with 22% lower objective gaps. NVIDIA's cuOpt optimization engine has found ...

Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...

1 School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou, China. 2 School of Science and Technology, Hunan University of Technology, Zhuzhou, China. To address the multicoupling ...

ABSTRACT: A hyperbolic model for the diffusion of proteins through the blood-cerebrospinal fluid (CSF) barrier revolutionized clinical neurochemistry thirty years ago. The regression curves were ...

A general-purpose Model Context Protocol (MCP) server for solving combinatorial optimization problems with logical and numerical constraints. This server provides a unified interface to multiple ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Mixed-integer nonlinear programming (MINLP) optimisation constitutes a critical methodology in tackling complex decision-making problems where both discrete choices and continuous variables are ...

Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where ...