【Objective】

2

In order to solve the problem that the traditional Ant Colony Optimization (ACO) algorithm updates the same map

resulting in the inability of parallel planning

a parallel multi-objective optimization submarine cable route planning algorithm is proposed in this paper

which realizes the precise planning of local areas.

【Methods】

2

In this paper

the grid map of the target sea area is divided into multiple grid subgraphs by the idea of divide and conquer

and a parallel multi-objective optimization submarine cable route algorithm model is established

and the key parameters of the model are optimized. Then

the Parallel Ant Colony Optimization (PACO) algorithm is used to carry out the submarine cable route planning under the optimal model parameters

and the submarine cable route scheme solved by Pareto frontier is counted.

【Results】

2

The simulation results show that the parallel multi-objective optimization model obtains the best search ability and efficiency when the number of blocks is 6 and the size of ant colony is 150. The PACO algorithm can save 33.9% of the cost of submarine cable route compared with the traditional ACO algorithm under the same risk conditions

and the cost of routes is smaller than the traditional ant colony algorithm. The maximum cost of routes is also reduced by 20.6% compared with the minimum cost of the traditional ACO algorithm

and the corresponding risk is reduced by 65.8%.

【Conclusion】

2

In multi-objective submarine cable route planning

compared to the traditional ACO algorithm

the PACO algorithm not only achieves better planning results but also improves computational efficiency by at least 8 times.