Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. Now he is Reader in Modelling and Optimization at Middlesex University London, Adjunct Professor at Reykjavik University (Iceland) and Guest Professor at Xi'an Polytechnic University (China). He is the IEEE CIS Chair for the Task Force on Business Intelligence and Knowledge Management and Director of International Consortium for Optimization and Modelling in Science and Industry (iCOMSI).
Talk Title Nature-Inspired Metaheuristics for Optimization
Nature-inspired metaheuristic algorithms have become effective tools for optimization concerning engineering designs, data minibg and computational intelligence. Nature provides a rich source of inspiration for ingenious problem-solving. Algorithms based on characteristics of bats, cuckoos, fireflies, birds, ants and bees have demonstrated their flexibility and effectiveness. However, there exist many challenging issues in this area. This talk focuses on the recent developments and highlights some key issues in swarm intelligence and nature-inspired metaheuristics for optimization.