The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get ...

Over the course of my 25-year career in the mathematical optimization software industry, I’ve lost count of how many times I’ve been asked this question: “Can you tell me what mathematical ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

Power consumption is a major source of pain for emerging complex SOC designs, particularly in battery sensitive applications requiring ultra low power. Not surprisingly, this area was the topic with ...

Quantum computers have already managed to surpass ordinary computers in solving certain tasks - unfortunately, totally useless ones. The next milestone is to get them to do useful things. Researchers ...

Optimizations in programming have mostly been associated with more efficient data structures or algorithms. Any optimization that uses hardware resources explicitly is generally considered premature, ...

We walk through an optimization problem step by step, clearly explaining how to identify variables, set up the correct ...

DETROIT--(BUSINESS WIRE)--Heartland has revolutionized plot mapping technology to drive efficiency for farming operations across the world. Its ReMap technology will reduce the time, money, energy, ...