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.

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 ...

While gate model quantum computing holds immense promise for tomorrow, quantum annealing systems are solving complex optimization problems for enterprises today. You’ve heard that quantum computing ...

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

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...

GPT-5.2 Pro delivers a Lean-verified proof of Erdős Problem 397, marking a shift from pattern-matching AI to autonomous ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, performance, and real-world applicability by introducing FlexQAOA, a hybrid ...

FICO Xpress 9.8 features a GPU-accelerated implementation of the hybrid gradient algorithm, yielding up to 50x speedups. The hybrid gradient algorithm is useful for getting faster solutions to ...