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Hybrid Adaptive Robust Optimization Strategy for EWIS High Dimensional systems (HAROS-HD)
Start date: Jan 1, 2014, End date: Sep 30, 2015 PROJECT  FINISHED 

"Complexity in modern aircrafts is increasing significantly. They incorporate more electric systems since other subsystems that used to be pneumatic or hydraulic are being replaced by electric systems. As a consequence, the wire harnesses that are used to connect those systems to each other must also convey more signals. The industrial-grade wiring harness acts as the central nervous system to many device and vehicle electronics designs, particularly in the aeronautic and aerospace segments. As applications become increasingly complex, innovation in wiring harness design and manufacturing techniques becomes more critical. This project will research and implement new methods for more efficiently driving design data toward fully automated design optimization so to better analyse costs, to help ensure the successful design and manufacture of new wiring harness products.For this purpose, the goal of this project is to link the unique state-of-the-art surrogate modelling technologies available at Noesis to develop new surrogate-based optimization techniques and software solutions suitable to solve wire harness large scale optimization problems. The resulting hybrid, adaptive and robust optimization strategy will allow optimization of high dimensional systems (HAROS-HD, Hybrid Adaptive Robust Optimization Strategy for High Dimensional systems) by means of smart adoption of model order reduction techniques coupled with surrogate models.The main advantages of this approach include:-Design engineers do not need to spend time and effort trying to understand their design space before choosing a suitable optimization algorithm. HAROS-HD will learn about the design space and employ the appropriate algorithms as it proceedstoward finding an optimized solution.-Design engineers are not required to be experts in optimization algorithms and applications, because HAROS-HD will intelligently adapt the optimization strategy by selecting the most appropriate method to use."

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