S-BORM: reliability-based optimization of general systems using buffered optimization and reliability method

Byun, J.-E. , de Oliveira, W. and Royset, J. O. (2023) S-BORM: reliability-based optimization of general systems using buffered optimization and reliability method. Reliability Engineering and System Safety, 236, 109314. (doi: 10.1016/j.ress.2023.109314)

Abstract

Reliability-based optimization (RBO) is crucial for identifying optimal risk-informed decisions for designing and operating engineering systems. However, its computation remains challenging as it requires a concurrent task of optimization and reliability analysis. Moreover, computation becomes even more complicated when considering performance of a general system, whose failure event is represented as a link-set of cut-sets. This is because even when component events have smooth and convex limit-state functions, the system limit-state function has neither property, except in trivial cases. To address the challenge, this study develops an efficient algorithm to solve RBO problems of general system events. We employ the buffered optimization and reliability method (BORM), which utilizes, instead of the conventional failure probability definition, the buffered failure probability. The proposed algorithm solves a sequence of difference-of-convex RBO models iteratively by employing a proximal bundle method. For demonstration, we design various numerical examples with increasing complexity that include up to 10,062 cut-sets, which are solved by the proposed algorithm within a reasonable computational time with high accuracy. We also demonstrate the algorithm’s robustness by performing extensive parametric studies.

• Item Type: Articles
• Additional Information: The research of the first author is in part supported by the Humboldt Research Fellowship for Postdoctoral Researchers from Alexander von Humboldt Foundation, Germany. The second author acknowledges financial support from the Gaspard-Monge Program for Optimization and Operations Research (PGMO) project “SOLEM - Scalable Optimization for Learning and Energy Management”. The research of the third author is supported in part by the Air Force Office of Scientific Research, Mathematical Optimization, United States (21RT0484).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Byun, Dr Ji-Eun

Creator Roles

Byun, J.-E.: Writing – original draft, Visualization, Software, Formal analysis

• Authors: Byun, J.-E., de Oliveira, W., and Royset, J. O.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• Journal Name: Reliability Engineering and System Safety
• Publisher: Elsevier
• ISSN: 0951-8320
• ISSN (Online): 1879-0836
• Published Online: 21 April 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Reliability Engineering and System Safety 236: 109314
• Publisher Policy: Reproduced under a Creative Commons License