Uncertainty plays a critical role in engineering design as even a small amount of uncertainty could make an optimal design solution infeasible. The goal of robust optimization is to find a solution that is both optimal and insensitive to uncertainty that may exist in parameters and design variables. In this paper, a novel approach, Sequential Quadratic Programing for Robust Optimization (SQP-RO), is proposed to solve single-objective continuous nonlinear optimization problems with interval uncertainty in parameters and design variables. This new SQP-RO is developed based on a classic SQP procedure with additional calculations for constraints on objective robustness, feasibility robustness, or both. The obtained solution is locally optimal and robust. Eight numerical and engineering examples with different levels of complexity are utilized to demonstrate the applicability and efficiency of the proposed SQP-RO with the comparison to its deterministic SQP counterpart and RO approaches using genetic algorithms. The objective and/or feasibility robustness are verified via Monte Carlo simulations.
Skip Nav Destination
ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 12–15, 2012
Chicago, Illinois, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-4502-8
PROCEEDINGS PAPER
Sequential Quadratic Programming for Robust Optimization With Interval Uncertainty Available to Purchase
Jianhua Zhou,
Jianhua Zhou
University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China
Search for other works by this author on:
Shuo Cheng,
Shuo Cheng
University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China
Search for other works by this author on:
Mian Li
Mian Li
University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China
Search for other works by this author on:
Jianhua Zhou
University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China
Shuo Cheng
University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China
Mian Li
University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China
Paper No:
DETC2012-70139, pp. 1087-1100; 14 pages
Published Online:
September 9, 2013
Citation
Zhou, J, Cheng, S, & Li, M. "Sequential Quadratic Programming for Robust Optimization With Interval Uncertainty." Proceedings of the ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3: 38th Design Automation Conference, Parts A and B. Chicago, Illinois, USA. August 12–15, 2012. pp. 1087-1100. ASME. https://doi.org/10.1115/DETC2012-70139
Download citation file:
8
Views
Related Proceedings Papers
Related Articles
The Merits of a Parallel Genetic Algorithm in Solving Hard Optimization Problems
J Biomech Eng (February,2003)
Optimization of Controllers for Gas Turbine Based on Probabilistic Robustness
J. Eng. Gas Turbines Power (September,2009)
Sequential Quadratic Programming for Robust Optimization With Interval Uncertainty
J. Mech. Des (October,2012)
Related Chapters
Advances in the Stochastic Modeling of Constitutive Laws at Small and Finite Strains
Advances in Computers and Information in Engineering Research, Volume 2
Utility Function Fundamentals
Decision Making in Engineering Design
Feedback-Aided Minimum Joint Motion
Robot Manipulator Redundancy Resolution