Surrogate modelling and optimization using shape-preserving response prediction: A review. Issue 3 (3rd March 2016)

• Record Type: Journal Article
• Authors: Leifsson, Leifur; Koziel, Slawomir
• Is Part Of: Engineering optimization. Volume 48:Issue 3(2016)
• Page Start: 476
• Page End: 496
• Publication Date: 2016-03-03
• Subjects: shape-preserving response prediction -- surrogate modelling -- surrogate-based optimization -- microwave engineering -- aerodynamic shape optimization; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2015.1016509
• Languages: English
• ISSNs: 0305-215X

Abstract

Abstract : Computer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computational expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem with conventional optimization algorithms. A promising approach to alleviate these difficulties is surrogate-based optimization (SBO). Among proven SBO techniques, the methods utilizing surrogates constructed from corrected physics-based low-fidelity models are, in many cases, the most efficient. This article reviews a particular technique of this type, namely, shape-preserving response prediction (SPRP), which works on the level of the model responses to correct the underlying low-fidelity models. The formulation and limitations of SPRP are discussed. Applications to several engineering design problems are provided.