University of Tennessee researchers James Ostrowski and Rebekah Herrman are developing quantum-computing tools to tackle multi-stage stochastic decision problems in fields like energy, logistics, and ...

Learn how to solve boundary value problems in Python using the finite difference method! 🐍📐 This tutorial walks you step-by-step through setting up the problem, discretizing the domain, and ...

We walk through an optimization problem step by step, clearly explaining how to identify variables, set up the correct function, apply derivatives, and find maximum or minimum values. Each step is ...

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 ...

In this talk, I will give a high-level tutorial on graphs of convex sets, with emphasis on their applications in robotics, control, and, more broadly, decision making. Mathematically, a Graph of ...

Is your feature request related to a problem? Please describe. I find it hard to translate the help given in FAQ on Optimization/AD into code that actually performs a parameter optimization. I propose ...

What if the next new mathematical discovery didn’t come from a human mind, but from an AI? Imagine a machine not just crunching numbers but proposing original solutions to problems that have baffled ...

Olivera Ciraj Bjelac, IAEA Department of Nuclear Sciences and Applications To support hospitals and specialists around the world in meeting their safety standards requirements, the IAEA has produced a ...

Abstract: Several interesting problems in multirobot systems can be cast in the framework of distributed optimization. Examples include multirobot task allocation, vehicle routing, target protection, ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...