An axiomatic system engineering design method based on NSGA-II algorithm applied to complex systems

This study proposes an integrated framework that combines Axiomatic Design with Model-Based Systems Engineering, incorporating NSGA-II as an intelligent optimization engine. The framework constructs a multi-level traceability matrix linking requirements, functions, behaviors, and structural elements...

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Bibliographic Details
Published in:Scientific reports Vol. 15; no. 1; pp. 31766 - 17
Main Authors: Zhang, Xiaoqian, Zhang, Qinghai, Zhao, Qingjian, Zhao, Shuang, Zhao, Yanan, Guo, Yang, Zhao, Zhengxu, Song, Liqiang
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 28.08.2025
Nature Publishing Group
Nature Portfolio
Subjects:
639/166/987
639/166/988
Active Reflective Surface Control System
Axiomatic design
Control systems
Decomposition
Design optimization
Genetic algorithms
Humanities and Social Sciences
Methods
Model-Based Systems Engineering
Modularity
multidisciplinary
NSGA-II
Product development
Science
Science (multidisciplinary)
System design methodology
Systems engineering
NSGA-II
Active Reflective Surface Control System
Model-Based Systems Engineering
Axiomatic design
System design methodology
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:This study proposes an integrated framework that combines Axiomatic Design with Model-Based Systems Engineering, incorporating NSGA-II as an intelligent optimization engine. The framework constructs a multi-level traceability matrix linking requirements, functions, behaviors, and structural elements, and leverages NSGA-II to dynamically optimize the sequencing of the Design Structure Matrix, thereby enhancing the explicitness and visualization of coupling relationships. Rather than directly eliminating dependencies, the approach aims to support a more systematic modularity-oriented analysis. Implemented using SysML, the framework establishes formal mappings among the user, functional, behavioral, and physical domains to ensure bidirectional traceability. In parallel, coupling degrees are quantitatively assessed based on axiomatic design principles, and a multi-objective intelligent search is employed to accelerate convergence within large-scale design spaces. A case study on an active reflector control system demonstrates that the proposed NSGA-II–enhanced framework significantly reduces reliance on expert knowledge in DSM ordering, and exhibits clear advantages in coupling identification and modularity analysis for complex systems.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-17689-5