Researchers have developed a new, data-driven machine-learning technique that speeds up software programs used to solve complex optimization problems that can have millions of potential solutions.

New research from the University of Waterloo is making inroads on one of the biggest problems in theoretical computer science ...

Researchers developed a machine-learning-guided technique to solve complex, long-horizon planning problems more efficiently than some traditional approaches, while arriving at an optimal solution that ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

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

Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various components that must work together to make an effective and efficient robot, ...

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 ...

These optimizations not only improved resource utilization and minimized congestion but also enhanced power distribution, ...