Abstract: With the rapid development of science and technology, nonlinear equations and optimal control problems play an important role in a wide range of fields. However, in the current research, the ...

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.

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 ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

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 ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

We study some nonlinear optimal control problems under state constraint. We construct extremal flows by differential-algebraic equations to solve an optimal control problem subject to mixed ...

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 ...

In today’s fast-paced, ever-evolving world, the complexity of challenges faced in both business and everyday life requires a shift in how we approach problem solving. Traditional linear thinking, ...

Annealing processors (APs) are gaining popularity for solving complex optimization problems. Fully-coupled Ising model APs are especially valued for their flexibility, but balancing capacity (number ...