With the rapid expansion of the networked operation scale of China’s urban rail transit, the number of vehicles has increased ...

Imagine Jo: Everyone in Jo's life recognizes her as an outstanding problem solver. She's the type of person who seems capable ...

My graduate studies included learning about constraint-based optimization algorithms (such as linear programming) and ...

Leaders run the risk of losing their strategic edge by blindly pushing AI for the sake of AI. Companies can no longer win the ...

Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

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

Each year when MD+DI editors sit down to discuss Medtech Company of the Year prospects, the companies that rise to the top for us tend to be those that have had a transformational year either through ...

Abstract: This article studies distributed optimization problems whose goal is to minimize the sum of cost functions located among agents in a network, where communications are described by a ...

You probably don’t need more time. By Jancee Dunn When I look back on all the major decisions I’ve dithered over, I could scream. It took me a decade to commit to becoming a parent. I wavered for a ...

Search optimization now requires combining traditional SEO with AI-focused GEO and answer-driven AEO strategies AI search usage continues to grow, with 10% of US consumers currently using generative ...

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 ...