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An improved guide weight method for multi-constraints structural optimization design
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DOI：10.1016/j.istruc.2025.109058.png)
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Abstract
En 中文
The guide-weight method (GWM) is an effective approach for structural optimization, known for its exceptionally fast convergence rate. However, the inability to optimize multiple constraints simultaneously limits the effectiveness of this method. This study proposes an improved guide-weight method (MIGW) for multiconstraints structural optimization. Different from existing GWM, the proposed MIGW concurrently solves all Lagrange multipliers (variable lambda) for multi-constraints, enabling synchronously optimization under multiple constraints. Therefore, this method reduces the complexity of structural analysis and number of structural analyses. Additionally, the range of step length (variable alpha) for each design variable is also determined to ensure that the post-iteration values remain within the preset limits. Different alpha values are assigned to different design variables, enhancing the flexibility of the optimization process. The convergence speed is improved by comparing the guide weight with the weight to determine the iterative direction of the design variables. The performance of the proposed MIGW is evaluated using a ten-bar planar truss as a benchmark example. The results show that compared to the GWM and heuristic optimization algorithms, the number of analyses required by MIGW was reduced by 50 % and 178 times, respectively, while yielding similar results.
Keywords:
Guide-weight method
Structural optimization
Lagrange multipliers
Iteration direction
Step length