Fueled by a passion for mathematical optimization — the selection of a best element, with regard to selected criteria, from a set of available alternatives — Professor of Mathematics Adam Levy has published Stationarity and Convergence in Reduce-or-Retreat Minimization (Springer, 2012).
“It’s the culmination of my recent work in numerical optimization — ‘numerical’ is a code-word for ‘using computation’ — and also lays the groundwork for future research,” says Levy.
“I’ve brought my training in analysis to the theory of numerical optimization and developed a framework for understanding and studying a wide variety of numerical optimization methods; now under one umbrella for the first time. I was first motivated to move in the direction of numerical optimization by my desire to make my research accessible to my undergraduate students. The textbook I published a few years ago was an obvious step in that direction, and this latest work is an extension of that same undertaking.”
The book presents and analyzes a unifying framework for a wide variety of numerical methods in optimization.
