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Multi-Objective Optimization for Submarine Cable Route Planning Based on the Ant Colony Optimization Algorithm
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DOI：10.3390/photonics10080896.png)
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It is essential to design an appropriate submarine cable route to reduce costs and improve reliability. A methodology that can be used for multi-objective optimization in submarine cable route planning is proposed and numerically studied in this paper. The costs and risks are numerically assessed and mapped to the geographical map. The pheromone and heuristic functions of the ant colony optimization (ACO) algorithm are associated with the geographical map of costs and risks, which enables it to search for a submarine cable route with multi-objective optimization. The results show that the submarine cable route designed by the methodology can effectively avoid high-cost and high-risk regions, which means that the designed submarine cable route is cost-effective and highly reliability.
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