JOURNAL ARTICLE

An Enhanced Analytical Target Cascading and Kriging Model Combined Approach for Multidisciplinary Design Optimization

Ping JiangJianzhuang WangQi ZhouXiaolin Zhang

Year: 2015 Journal:   Mathematical Problems in Engineering Vol: 2015 Pages: 1-11   Publisher: Hindawi Publishing Corporation

Abstract

Multidisciplinary design optimization (MDO) has been applied widely in the design of complex engineering systems. To ease MDO problems, analytical target cascading (ATC) organizes MDO process into multilevels according to the components of engineering systems, which provides a promising way to deal with MDO problems. ATC adopts a coordination strategy to coordinate the couplings between two adjacent levels in the design optimization process; however, existing coordination strategies in ATC face the obstacles of complicated coordination process and heavy computation cost. In order to conquer this problem, a quadratic exterior penalty function (QEPF) based ATC (QEPF-ATC) approach is proposed, where QEPF is adopted as the coordination strategy. Moreover, approximate models are adopted widely to replace the expensive simulation models in MDO; a QEPF-ATC and Kriging model combined approach is further proposed to deal with MDO problems, owing to the comprehensive performance, high approximation accuracy, and robustness of Kriging model. Finally, the geometric programming and reducer design cases are given to validate the applicability and efficiency of the proposed approach.

Keywords:
Multidisciplinary design optimization Robustness (evolution) Kriging Mathematical optimization Process (computing) Computation Engineering design process Computer science Multidisciplinary approach Engineering Systems engineering Algorithm Mathematics Mechanical engineering

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15
Cited By
3.90
FWCI (Field Weighted Citation Impact)
24
Refs
0.95
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Probabilistic and Robust Engineering Design
Social Sciences →  Decision Sciences →  Statistics, Probability and Uncertainty
Optimal Experimental Design Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research
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