Strategies for adaptive optimization with aggregation constraints using interior-point methods. (June 2015)

• Record Type: Journal Article
• Authors: Kennedy, Graeme J.
• Is Part Of: Computers & structures. Volume 153(2015)
• Page Start: 217
• Page End: 229
• Publication Date: 2015-06
• Subjects: Design optimization -- Aggregation-constraints -- Kreisselmeier–Steinhauser function -- Adaptive optimization -- Stress-constrained mass-minimization; Structural engineering -- Data processing -- Periodicals; Electronic data processing -- Structures, Theory of -- Periodicals; 624.171
• DOI: 10.1016/j.compstruc.2015.02.024
• Languages: English
• ISSNs: 0045-7949

Abstract

Abstract: Constraint-aggregation methods are used in engineering optimization problems to approximately impose a bound on a quantity of interest in a differentiable manner. In this paper, we present strategies to adaptively solve aggregation-constrained problems. These adaptive techniques achieve a tighter bound approximation while also reducing the computational cost of optimization. We focus on two aggregation techniques: Kreisselmeier–Steinhauser (KS) aggregation, and induced exponential aggregation. We demonstrate that the proposed adaptive technique achieves significant computational savings compared to fixed-aggregation methods for a series of stress-constrained mass-minimization problems.