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This study presents a multi-objective optimization approach for the design of a two-stage helical gearbox, focusing on minimizing the overall axial length while maximizing transmission efficiency. A hybrid method combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with the entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed. NSGA-II is employed to generate a Pareto-optimal front considering geometric and performance constraints, while TOPSIS, integrated with entropy-based criteria weighting, is used to rank and select the most balanced design solution. The results demonstrate that the proposed hybrid framework effectively captures the trade-off between structural compactness and mechanical performance, offering valuable insights for optimal gearbox design in constrained industrial applications.

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Efficiency–Length Trade-Off in Two-Stage Helical Gearbox Design: A Hybrid NSGA-II and Entropy–TOPSIS Approach

  • 会议论文

  • 发表日期：

    2026年

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  • Vu Duc Binh,
  • Vu Ngoc Pi,
  • Dinh Van Thanh,
  • Nguyen Manh Cuong

摘要

This study presents a multi-objective optimization approach for the design of a two-stage helical gearbox, focusing on minimizing the overall axial length while maximizing transmission efficiency. A hybrid method combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with the entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed. NSGA-II is employed to generate a Pareto-optimal front considering geometric and performance constraints, while TOPSIS, integrated with entropy-based criteria weighting, is used to rank and select the most balanced design solution. The results demonstrate that the proposed hybrid framework effectively captures the trade-off between structural compactness and mechanical performance, offering valuable insights for optimal gearbox design in constrained industrial applications.