Multi-Objective Collaborative Optimization of Central Support Components in Steel Structures Integrating NSGA-II and Nested Topology Optimization

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Authors

  • Lei Han Shandong University of Engineering and Vocational Technology, China
  • Heng Zheng Shandong Polytechnic, China
  • Jianying Weng Shandong University of Engineering and Vocational Technology, China
  • Xue Li Shandong University of Engineering and Vocational Technology, China

Abstract

This paper presents a multi-objective collaborative optimization framework for central support member in steel structures, aiming to simultaneously minimize structural mass and compliance. Traditional design methods often optimize a single objective, therefore limiting overall performance. To address this, we integrate the NSGA-II genetic algorithm with the solid isotropic material with penalization (SIMP) topology optimization method within hierarchical bi-level optimization framework. NSGA-II performs a global search for optimal macro-level geometric parameters, while SIMP optimizes the micro-level material distribution under the given geometries. The interaction between both levels enables a comprehensive trade-off between lightweight design and structural stiffness. Case studies on various support types demonstrate that the proposed method effectively reduces structural mass while enhancing stiffness, confirming its robustness and broad applicability. The Pareto front achieves a high hypervolume (HV) index, indicating excellent solution diversity and quality. This approach provides an intelligent and efficient pathway for the high-performance, lightweight design of steel structures.

Keywords:

steel structure, central support member, multi-objective optimization, topology optimization, NSGA-II algorithm, collaborative optimization

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