Professor David Wolfe Corne

David Wolfe Corne, Ph.D. is Director of Research for the School of Mathematics and Computer Sciences (MACS) at Heriot-Watt University, Edinburgh, UK. MACS is pre-eminent in Scotland in the Mathematical and Computer Sciences, compromising part of the Maxwell Institute for Mathematical Sciences (a joint institute with the University of Edinburgh), and a number of pioneering research centers.
 
David also leads the Intelligent Systems Laboratory, which maintains a portfolio of substantial achievements that range through fundamental models of computation, computational systems biology, computational neuroscience, and advanced methods for design, optimization, and data mining. Following several years as a research associate in the Department of Artificial Intelligence at the University of Edinburgh, which led to the extremely successful problem solving approach now called “hyper-heuristics”, David was a Lecturer (1997) and then Reader (2003) at the University of Reading. He then took up a Chair in Computer Science at the University of Exeter in 2004, and moved to his current post in 2006.
 
His continuing research agenda concerns novel methods for optimization, data mining, and machine learning, as well as strategies for solving large scale problems, with particular interests in multicriteria problems.
 
David serves on the editorial boards of many prestigious journals, including Applied Intelligence, Applied Soft Computing, International Journal of Bioinformatics Research and Applications, Journal of Computational Intelligence in Bioinformatics, Evolutionary Computation, IEEE Transactions on Evolutionary Computation, International Journal of Hybrid Intelligent Systems, International Journal of Metaheuristics, Natural Computing, and Theoretical Computer Science — C (Natural Computing).
 
His books include New Ideas in Optimization, Creative Evolutionary Systems, and Evolutionary Computation in Bioinformatics. His papers include Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy, The Pareto-Envelope based Selection Algorithm for Multiobjective Optimization, A Promising GA Approach to Jon Shop Scheduling, Rescheduling, and Open-Shop Scheduling Problems, On Metrics for Comparing Non-Dominated Sets, M-PAES: a memetic algorithm for multiobjective optimization, Reducing Local Optima in Single-Objective Problems by Multiobjectivization, A large benchmark dataset for web document clustering, and Solving the Modular Exam Scheduling Problem with Genetic Algorithms.