To address the challenges of dense structural layouts, limited path feasibility, and stringent assembly constraints in cable routing within complex compartments of aerospace equipment, this paper proposes a cable path planning method that integrates Bidirectional Crossing Line Pruning (BCLP) with an improved ant colony optimization (IACO) algorithm. First, a hierarchical activation strategy for key obstacles is realized by constructing primary and extended crossing lines. On this basis, the BCLP algorithm is introduced, combining global perspective with local reduction capability to significantly reduce the complexity of the search space. Second, in line with cable assembly process requirements, a composite heuristic function is formulated by integrating obstacle-crossing cost and bending penalty. Additionally, a multi-objective-driven pheromone update model is developed to enhance the routing process’ feasibility and convergence performance. Experimental results across various aerospace cabling simulation scenarios demonstrate that the proposed method achieves an average reduction of 19.6% in multi-objective process cost and a 68.5% improvement in convergence efficiency compared to traditional visual graph methods combined with standard ACO. The approach provides effective support for the automation and intelligent planning of cable layouts in complex environments, offering strong potential for engineering applications.
Li et al. (Fri,) studied this question.