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 ...

Research paper by Bjørnar Luteberget and Giorgio Sartor wins 2024 FICO® Xpress Best Paper Award; the algorithm is now in FICO® Xpress Solver “When solving a very large computational problem, ...

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

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 ...

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 ...

BEAVERTON, Ore.--(BUSINESS WIRE)--Gurobi Optimization, LLC, the leader in decision intelligence technology, in collaboration with Dr. Joel Sokol, Harold E. Smalley Professor in Georgia Tech’s H.

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 ...