About the Authors (short biographies as of 2006):
Holger H. Hoos is an Associate Professor at the Computer Science Department of the University of British Columbia (Canada). His Ph.D. thesis on stochastic local search algorithms for computationally hard problems in artificial intelligence, completed in 1998 at Darmstadt University of Technology (Germany), received the ‘Best Dissertation Award 1999’ of the German Informatics Society. He has been working on the design and empirical analysis of stochastic local search algorithms since 1994, and his research in this area has been published in book chapters, journal articles and at major conferences in AI and OR. Holger’s research interests are currently focused on topics in artificial intelligence, bioinformatics, empirical algorithmics and computer music. At the University of British Columbia, he is a founding member of the Bioinformatics, Empirical & Theoretical Algorithmics Laboratory (BETA-Lab), a member of the Laboratory for Computational Intelligence (LCI), and a faculty associate of the Peter Wall Institute for Advanced Studies.
Thomas Stützle is a Research Associate of the Belgian F.N.R.S. and working at the IRIDIA group of the Université Libre de Bruxelles (Belgium). He received an M.Sc. degree in Industrial Engineering and Management Science at the University of Karlsruhe and a Ph.D. from the Computer Science Department of Darmstadt University of Technology. He was a postgraduate fellow at the Department of Statistics and Operations Research, Universidad Complutense de Madrid and a Marie Curie Fellow at IRIDIA, Université Libre de Bruxelles. Thomas has been involved in several EU funded projects on the study of stochastic local search techniques and his research is published in various journals, book chapters and conferences in OR and AI. His current research focuses on methodologies for the engineering of SLS algorithms, the automatization of the design and the tuning of SLS algorithms, large-scale experimental studies of SLS algorithms and applications of SLS algorithms to multiobjective optimization problems.
Authors' Web Pages (for current/additional information):