Bayesian and High-Dimensional Global Optimization

Anatoly Zhigljavsky has received his BSc, MSc and PhD degrees in mathematics and statistics at Faculty of Mathematics, St.Petersburg State University. He became professor of statistics at the St.Petersburg State University in 1989. Since 1997 he is a professor, Chair in Statistics at Cardiff University.  Anatoly Zhigljavsky is the author or co-author of 11 monographs on the topics of time series analysis, stochastic global optimization, optimal experimental design and dynamical systems; he is the editor/co-editor of 9 books on various topics and the author of more than 150 research papers in refereed journals. He has organized several major conferences on time series analysis, experimental design and global optimization. In 2019, he has received a prestigious Constantine Caratheodory award by the International Society for Global Optimization for his contribution to stochastic optimization.Antanas Žilinskas is member of Lithuanian Academy of Sciences and professor of informatics at the Institute of Data Science and Digital Technologies of Vilnius university. His research interests include global and multi-objective optimization, visualization of multidimensional data, and optimal engineering design. He is author or co-author of several well-known monographs in optimization. His scientific achievements in global optimization are marked by the Caratheodory prize of the International Society of Global Optimization (2017). Prof. Žilinskas is a member of editorial boards of numerous international scientific journals. He also paid a lot of attention to teaching students and organizing studies of informatics, has prepared several textbooks on optimization and informatics.

“The book is well and intelligibly written. The text is accompanied by a lot of nice pictures, each chapter concludes with a list of references. The book is intended for a wide range of readers interested in the theoretical aspects of global optimization, methodology or applications of global optimization.” (Ctirad Matonoha, Mathematical Reviews, April, 2022)“The book is well written, the presentation is clear and easy to follow. Numerous pictures enrich the content and make it easier to understand. I recommend this book to the researchers in the area of global optimization – it may serve as a nice survey on the recent results about the randomized methods in GO. I also think that it would be very useful for graduate students … as well as for the practitioners focused on the methodology.” (Marcin Anholcer, zbMATH 1473.90134, 2021)

• 1 Space-filling in high-dimensional sets.- 2 Bi-objective decisions and partition based methods in Bayesian global optimization.- 3 Global random search in high dimensions.