Lightweight Design and Research of Electric Towing Winch Based on Kriging-NSGA-III-TOPSIS Multi-Objective Optimization Technology

To address the challenges of weight redundancy, low material utilization, and excessive performance margins in the design of electric cable-hauling machines, this study proposes a novel multi-objective optimization framework. The framework integrates Latin hypercube experimental design, Kriging surrogate modeling, a Non-dominated Sorting Genetic Algorithm III (NSGA-III), and a coupled TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach. A high-fidelity finite element model based on extreme operating conditions was established to simulate the performance of the electric towing winch. The Kriging model was employed to replace time-consuming finite element calculations, significantly improving computational efficiency. The NSGA-III algorithm was then utilized to search for the Pareto front, identifying a set of optimal solutions that balance multiple design objectives. Finally, the TOPSIS method was applied to select the most preferable solution from the Pareto front. The results demonstrate a 7.32% reduction in the overall mass of the towing winch, a 7.34% increase in the safety factor, and a 4.57% reduction in maximum structural deformation under extreme operating conditions. These findings validate the effectiveness of the proposed Kriging-NSGA-III-TOPSIS strategy for lightweight design of ship deck winch machinery.