Surrogate-Assisted Evolutionary Optimisation (SAEOpt'16) Chairs' Welcome & Organization

It is our great pleasure to welcome you to the Workshop on Surrogate-Assisted Evolutionary Optimisation (SAEOpt). In many real world optimisation problems evaluating the objective function(s) is computationally expensive. Surrogate-assisted optimisation attempts to alleviate this problem by employing computationally cheap 'surrogate' models to estimate the objective function(s) or the ranking relationships between candidate solutions. Surrogate-assisted approaches have been widely used across the field of evolutionary optimisation, and successful applications include aerodynamic design optimisation, structural design optimisation, data-driven optimisation, chip design, drug design, robotics and many more. Despite recent successes in using surrogate-assisted evolutionary optimisation, there remain many challenges. In this workshop we aim to promote research on surrogate-assisted evolutionary optimisation, particularly the synergies between evolutionary optimisation and machine learning. We hope that the workshop will be of interest to researchers working on the applied and theoretical aspects of surrogate-assisted evolutionary optimisation.