恶劣气象海况下船舶航线的多变量多目标优化建模  

Multi-Variable-Multi-Objective Optimization of Ship Routes Under Rough Weather Condition

作　　者：李明峰 王胜正[1] 谢宗轩 LI Mingfeng;WANG Shengzheng;XIE Zongxuan(Merchant Marine College,Shanghai Maritime University,Shanghai 201306,China)

机构地区：[1]上海海事大学商船学院,上海201306

出　　处：《中国航海》2020年第2期14-19,30,共7页Navigation of China

基　　金：国家重点研发计划(2019YFB1600605);上海市科技创新行动计划社会发展领域项目(18DZ1206101);上海市曙光人才计划(15SG44)。

摘　　要：气象航线优化是一种复杂的多变量多目标问题。为解决该问题,提出一种可行的船舶气象航线优化方法,以航线转向点和每段航速为优化对象,以船舶特性和动态规避恶劣气象海况为约束条件,以最少航时和最低油耗为优化目标,建立船舶多变量、多动态约束、多目标的气象航线优化模型,并以强度帕累托多目标遗传进化算法为理论基础,构建基于气象海况影响因子的加权惩罚适应度评估模型,优化解的选择空间,实现对该问题的有效求解。试验结果证明:通过同时对航路和航速进行优化,不仅可规避时空动态变化的恶劣气象海况,而且可得到各种用户偏好情况下的气象航线,对实现船舶的智能航行具有重要的意义。Weather route optimization proposes comprehensively optimized route and speed in terms of multiple objects such as fuel consumption,navigation time and navigation safety rather than simply giving safe route and speed as traditional weather navigation does.A multi-variable multiple dynamic constraint and multi-objective weather routing optimization model is established.The model takes the route waypoints and speed of each segment as the control parameters,the ship characteristics and dynamic avoidance of rough weather conditions as the constraints,and the minimum voyage time and minimum fuel consumption as the object.In order to solve the optimization problem effectively,based on the theory of Intensity Pareto Multi-Objective Genetic Evolutionary Algorithms,an evaluation model of penalty-fitness against weather influencing factors is constructed to optimize the choice space of solutions.The proposed method delivers optimized routes and speeds for various user preferences while avoiding rough weather conditions that dynamically changes with time and space,which is of great significance to realize the intelligent navigation of ships.

关 键 词：多目标遗传算法 气象导航 航线优化 智能航行 

分 类 号：U692.31[交通运输工程—港口、海岸及近海工程]