Research and investment in artificial intelligence (AI) have rapidly expanded over the past decade. The International Data Corporation predicts that global spending on cognitive and AI systems will ...

Global optimisation methods and algorithms are pivotal in addressing complex problems where the objective function is often non‐convex, multi‐modal, or even presented as a black‐box with expensive ...

Students will learn about the most common numerical optimization algorithms for solving smooth unconstrained and constrained optimization problems. They will understand the theoretical foundation and ...

"What's the difference between mathematical optimization and machine learning?" This is a question that — as the CEO of a mathematical optimization software company — I get asked all the time.

The Covid-19 pandemic has triggered a wave of severe economic disruption around the world, causing widespread chaos, profound changes in the business landscape and overwhelming operational challenges.

- When the problem is large-scale and high-dimensional (involving a vast number of variables), the computational complexity increases explosively, making the calculations infeasible. - Data may be ...

Professor Ruszczynski’s interests are in the theory, numerical methods and applications of stochastic optimization. He is author of "Nonlinear Optimization", "Lectures on Stochastic programming", and ...

In large retail operations, category management teams spend significant time deciding which product goes onto which shelf and in which order. Shelf space is very expensive real estate in retail.