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This study presents a hybrid optimization framework integrating the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Multi-Attributive Border Approximation area Comparison (MABAC) method to address the multi-objective design of a two-stage helical gearbox with a split output stage. The proposed approach simultaneously minimizes the cross-sectional area of the gearbox housing and maximizes its mechanical efficiency, addressing critical trade-offs in compactness and performance. NSGA-II is employed to generate a Pareto-optimal front, capturing diverse design alternatives under geometric, strength, and performance constraints. Subsequently, the MABAC method is utilized to rank the Pareto-optimal solutions and support informed decision-making. The results demonstrate the effectiveness of the proposed hybrid method in identifying optimal configurations that enhance design compactness while maintaining high transmission efficiency. This research contributes a practical and flexible approach for the systematic optimization of complex gearbox systems.

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A Hybrid Evolutionary-MCDM Approach for Multi-Objective Optimization of Split-Output Gearbox Design

  • 会议论文

  • 发表日期：

    2026年

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  • Tran Huu Danh,
  • Le Thi Phuong Thao,
  • Dinh Van Thanh,
  • Luu Anh Tung

摘要

This study presents a hybrid optimization framework integrating the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Multi-Attributive Border Approximation area Comparison (MABAC) method to address the multi-objective design of a two-stage helical gearbox with a split output stage. The proposed approach simultaneously minimizes the cross-sectional area of the gearbox housing and maximizes its mechanical efficiency, addressing critical trade-offs in compactness and performance. NSGA-II is employed to generate a Pareto-optimal front, capturing diverse design alternatives under geometric, strength, and performance constraints. Subsequently, the MABAC method is utilized to rank the Pareto-optimal solutions and support informed decision-making. The results demonstrate the effectiveness of the proposed hybrid method in identifying optimal configurations that enhance design compactness while maintaining high transmission efficiency. This research contributes a practical and flexible approach for the systematic optimization of complex gearbox systems.