Robust Design Optimization Method for Engineering System

Richa Verma, Dinesh Kumar, Kazuma Kobayashi and Syed Alam ()
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Richa Verma: Indian Institute of Technology
Dinesh Kumar: University of Bristol
Kazuma Kobayashi: Missouri University of Science and Technology
Syed Alam: Missouri University of Science and Technology

A chapter in Handbook of Smart Energy Systems, 2023, pp 1325-1332 from Springer

Abstract: Abstract Robust optimization is a method for optimization under uncertainties in engineering systems and designs for applications ranging from aeronautics to nuclear. In a robust design process, parameter variability (or uncertainty) is incorporated into the engineering systems’ optimization process to assure the systems’ quality and reliability. This chapter focuses on a robust optimization approach for developing robust and reliable advanced systems and explains the framework for using uncertainty quantification and optimization techniques. For the uncertainty analysis, a polynomial chaos-based approach is combined with the optimization algorithms MOSA (Multi-Objective Simulated Annealing), and the process is discussed with a simplified test function. For the optimization process, gradient-free genetic algorithms are considered as the optimizer scans the whole design space, and the optimal values are not always dependent on the initial values.

Keywords: Machine Learning; Optimizations; Uncertainty quantification; Reliability analysis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-97940-9_206

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DOI: 10.1007/978-3-030-97940-9_206

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