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.

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 ...

Russian scientists from Lobachevsky State University of Nizhni Novgorod have improved the method of global optimization by offering the so-called "diagonal approach." The goal of global optimization ...

DUBLIN--(BUSINESS WIRE)--Research and Markets(http://www.researchandmarkets.com/research/799091/deterministic_oper) has announced the addition of John Wiley and Sons ...

- 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 ...