基于Pareto蚁群算法的船舶风险规避路径优化

船舶在海上航行时，一直面临着海上运输风险的威胁，为了降低海上运输风险同时考虑船舶经济效益，本文建立了以运输风险最小和航行成本最小的双目标路径优化模型，实现船舶风险规避.运用栅格法构建环境模型，为相应的栅格路径赋予航行成本和运输风险，并设计了一种基于Pareto最优解集和NSGA小生境方法的多目标蚁群算法.以印度洋海域的2条航线为案例，以经典单目标蚁群算法为对比，验证了模型和算法的有效性.结果表明，该模型和算法在解决船舶风险规避路径优化问题上具有良好的效果，能为决策者制定船舶海上运输风险规避路径提供决策参考.

Ship Risk Aversion Path Optimization Based on Pareto Ant Colony Algorithm

When ships are sailing at sea, they are always facing the threat of maritime transportation risk. In order to reduce the risk in maritime transportation while taking into account the economic benefits of the ship, a biobjective path optimization model is established. The two objectives of the model are the minimization of the cost of navigation and the total risk of the ship route. Grid method is used to construct the environment, and the cost of navigation and the risk in maritime transportation are assigned to the corresponding raster path. A multi-objective ant colony algorithm based on Pareto optimal solution set and NSGA niche method is designed. As a case study, the proposed model and algorithm are applied for optimizing the ship routes in the area of Indian Ocean. The classic single-target ant colony algorithm is also used as the comparison object to verify the validity of algorithm. The results show that the model and algorithm have a good effect in solving the ship risk aversion path optimization problem, and can provide decision- making reference for decision makers to formulate the marine shipping route.