Abstract: Model predictive control (MPC) typically includes a terminal constraint to guarantee stability of the closed-loop system under nominal conditions. In linear MPC, this constraint is generally ...

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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 ...

Influence Maximization (IM) is a fundamental problem in network science with applications in viral marketing, information dissemination, cybersecurity, and epidemiology. Classical IM solvers often ...

In recent years, the prospect of real-world quantum computing has raised hopes for solving hard combinatorial optimisation problems, leading to tremendous theoretical work on developing and analysing ...

The Simplex method is a foundational algorithm in linear programming, widely used for solving optimization problems where the goal is to maximize or minimize a linear objective function subject to a ...

ABSTRACT: This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary ...

Forbes contributors publish independent expert analyses and insights. Caroline Castrillon covers career, entrepreneurship and women at work. Non-linear careers represent a fundamental shift in how we ...

Dozens of neo-Nazis are fleeing Telegram and moving to a relatively unknown secret chat app that has received funding from Twitter founder Jack Dorsey. While ISD stopped short of naming SimpleX in its ...

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution ...

What did you dream of doing when you were 16 years old? I wanted to drive a car and travel the world. But American mathematician Ray Solomonoff had more ambitious goals at that age. He wanted to find ...