An Examination of Organic Computing Strategies in Design Optimization
J. Decke. Organic Computing -- Doctoral Dissertation Colloquium 2023, kassel university press, (2023)
Zusammenfassung
In the field of design optimization, numerical equation solvers,
commonly used for finite element analysis and computational fluid dy-
namics, impose significant computational demands. The iterative nature
of design optimization, involving numerous simulations, magnifies re-
source requirements in terms of time, energy, costs, and greenhouse gas
emissions. Accelerating this process has been a long-standing research
challenge, driven by the potential for resource savings and the ability
to tackle increasingly complex problems. Recently, organic computing
methods have gained prominence as promising approaches to address
this challenge. This study aims to bridge the gap by integrating tech-
niques from deep learning, active learning, and generative learning into
the field of design optimization. The goal is to accelerate the design op-
timization process while addressing specific challenges such as exploring
large and complex design spaces and evaluating the advantages and con-
straints of these methods. This research has the potential to significantly
impact the industrial use of design optimization by providing faster and
more efficient tools.
