Abstract: Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). Among them, ...

From the UCSB The Current article "Innovative Hardware for Rapidly Solving High-order Optimization Problems" The rise of AI, graphic processing, combinatorial optimization, and other data-intensive ...

It remains an open question when a commercial quantum computer will emerge that can outperform classical (non-quantum) machines in speed and energy efficiency while solving real-world combinatorial ...

The year isn't over yet, but we've already seen record-breaking quantum computers, skyrocketing levels of investment, and demonstrations of real-world benefits. In all the hype about AI it can be easy ...

The leading approach to the simplex method, a widely used technique for balancing complex logistical constraints, can’t get any better. In 1939, upon arriving late to his statistics course at the ...

Like the rest of its Big Tech cadre, Google has spent lavishly on developing generative AI models. Google’s AI can clean up your text messages and summarize the web, but the company is constantly ...

CAMBRIDGE, U.K. – A small Microsoft Research team had lofty goals when it set out four years ago to create an analog optical computer that would use light as a medium for solving complex problems.

OpenAI said it, too, had built a system that achieved similar results. By Cade Metz Reporting from San Francisco An artificial intelligence system built by Google DeepMind, the tech giant’s primary ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

MicroAlgo Inc. announced its research on the Quantum Information Recursive Optimization (QIRO) algorithm, which aims to address complex combinatorial optimization problems using quantum computing.