Simulation-Based Optimization: Methods and Applications in Engineering Design
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (1 July 2022) | Viewed by 21947
Special Issue Editors
Interests: simulation-based design optimization; machine learning; dimensionality reduction; surrogate-modelling; multi-fidelity methods; optimization algorithms; uncertainty quantification; application of computational fluid dynamics
Special Issue Information
Dear Colleagues,
In the engineering design context, the demand for efficient products is constantly increasing. These products must respond to an ever-increasing number of specific and complex requirements. Over the last thirty years, engineering design has radically transformed thanks to the exponential development of IT and digital resources. This has allowed the transformation of the classical approach of design, built, and test toward a more efficient simulation-based design optimization (SBDO) process, integrating numerical solvers, design modification methods, optimization algorithms, and also uncertainty quantification methods. The results obtained through the SBDO process are often a compromise between its efficiency (speed in achieving the optimum) and effectiveness (accurate simulations, requiring high-fidelity/computationally expensive solvers). Despite the advancement of computational resources, the challenge is to improve the SBDO framework (as a whole or its single components) in order to efficiently achieve accurate optimal solutions in solving complex engineering design problems.
The aim of this Special Issue is to collect state-of-the-art research on simulation-based optimization methods and their applications to complex engineering design problems. Relevant topics, methods, and applications are included in (but not limited to) the list below
- Single- and multiobjective optimization algorithms;
- Multidisciplinary optimization;
- Metamodeling and machine learning in SBDO;
- Multi-fidelity methods;
- Dimensionality reduction;
- Optimization under uncertainty;
- Design modification methods;
- Engineering design of aeronautical, aerospace, electrical, mechanical, naval applications.
Dr. Andrea Serani
Dr. Riccardo Pellegrini
Guest Editors
Manuscript Submission Information
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