Black Box Optimization, Machine Learning and No-Free Lunch Theorems

Springer Optimization and Its Applications

Prof. Panos Pardalos (USA), Prof. Varvara Rasskazova (Russland) und Prof. Michael Vrahatis (Griechenland) haben Prof. Bartz-Beielstein eingeladen, einen Gastbeitrag in dem Buch „Black Box Optimization, Machine Learning and No-Free Lunch Theorems“ zu schreiben. Das Buch erscheint in der renommierten Reihe „Springer Optimization and Its Applications“.

Springer beschreibt die Buchreihe wie folgt:
Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics, engineering, medicine, economics and other sciences.

The series Springer Optimization and Its Applications aims to publish state-of-the-art expository works (monographs, contributed volumes, textbooks) that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization (convex and nonconvex), network flow problems, stochastic optimization, optimal control, discrete optimization, multi-objective programming, description of software packages, approximation techniques and heuristic approaches.