To address the high complexity and large-scale nature of ship cable routing, this study proposes a bilevel optimization approach for cable routing that takes into account channel constraints.

Focusing on cable routing design for multi-deck ships, a bilevel optimization framework is developed to decompose the problem into two subproblems. The upper-level problem formulates cable routing sequence optimization as a permutation problem, while the lower-level problem formulates cable path optimization under channel capacity constraints as a single-source path optimization problem. The proposed integrated optimization framework employs the genetic algorithm (GA) to solve the upper-level problem and the A-star algorithm to solve the lower-level problem. Case studies conducted in representative routing environments demonstrate the effectiveness of the proposed optimization algorithms.

The results demonstrate that the proposed bilevel optimization method effectively performs both routing-sequence optimization and path optimization for large-scale ship cable routing. The multimodal characteristics of the cable routing optimization problem are revealed. By dynamically updating channel capacities and coordinating routing sequence optimization, the proposed bilevel optimization method increases the number of successfully routed cables while reducing the total routing cost.

The results can provide a technical reference for ship cable routing design.