Organized by: Slawomir Koziel and Leifur Leifsson, Reykjavik University, Iceland.

Description:
The use of computer simulations is ubiquitous in contemporary engineering design. High-fidelity numerical models are very accurate but, at the same time, computationally expensive. Depending on the structure complexity and required accuracy level, evaluation time for a single design can take hours, days or even weeks. Therefore, direct use of high-fidelity simulations in the optimization loop may be prohibitive. On the other hand, in many cases, simulation-driven design is the only option due to complexity of the structure under consideration and the lack of analytical models and/or systematic design procedures. In such instances, computationally efficient design can be performed using surrogate-based optimization (SBO), where the highfidelity model is replaced by its computationally cheap but still reasonably accurate representation, a surrogate. The surrogate model can be created using various approximation schemes. The surrogate can also be knowledge-based, i.e., constructed from the low-fidelity model that enjoys the same physics as the high-fidelity one. One of the important goals of SBO procedures is to reduce the number of high-fidelity model evaluations, and, consequently, to lower the overall optimization cost. This mini-symposium aims at reviewing state-of-the-art and promoting new directions of surrogate-based and knowledge-based methodologies for efficient optimization of computationally expensive engineering problems.