Aim and Scope
Reduction of the design cycle and increase of products performance are nowadays the main challenges in engineering design. The intrinsic complexity of engineering design relies more and more on the development and assessment of new theoretical methodologies capable of reducing or even replacing the experimental load. Two main characteristics are usually required to theoretical methods: high-fidelity and low cost. In this preliminary phase, the use of evolutionary algorithms (EAs) or other meta-heuristics seems to be of key importance in a preliminary phase, due to their ability to broadly explore the design space. In addition, they have the ability to work with noisy objective functions without assumptions on continuity and with a high potential to find the global optimum of complex engineering problems. However, they usually involve a vast number of evaluations even for a small number of design variables, and, in some cases, the evaluation function is time -consuming, therefore the optimization problem can become unfeasible within current industrial time-to-market frameworks. To overcome this problem, EAs have been hybridized with meta-models, or surrogate models, in several works published in the last years, in order to substitute expensive evaluation functions.
The aim of this special session is to bring together researchers from different application fields working on evolutionary optimizations and other global optimization methods assisted by surrogate models. Authors are invited to submit papers on one or more of the following topics:
- Surrogate-assisted evolutionary optimization of engineering problems
- Surrogate-assisted robust optimization
- Surrogates for dealing with uncertainties and constrains in optimization
- Trust region methodologies for surrogate-assisted evolutionary optimization
- Supervised, semi-supervised and incremental learning for optimization
- Data-driven optimisation and sampling techniques
- Reduced order modelling and multi-fidelity surrogate modelling
All papers are to be submitted electronically at:
Please choose “Special Session on Surrogate-Assisted Global Optimization Methods for Expensive Engineering Design" as the topic of your paper. Please also notify the organizers of your submission. Submission deadline: December 20, 2013.
Dr Esther Andrés, Fluid Dynamics Branch, Spanish National Institute for Aerospace Technology (INTA), Spain. Email:
Dr Emiliano Iuliano, Fluid Dynamics Lab, Italian Aerospace Research Center (CIRA), Italy. Email: firstname.lastname@example.org
Prof Yaochu Jin, Department of Computing, University of Surrey, Guildford, UK. Email: email@example.com