不确定场景下船舶尾气排放监测无人机选址路径优化  

Optimization of drone location and routing for ship exhaust emissions detection under uncertain scenarios

作　　者：胡碟 胡志华[1] 李姚娜 HU Die;HU Zhihua;LI Yaona(Logistics Center,Shanghai Maritime University,Shanghai 201306,China)

机构地区：[1]上海海事大学物流研究中心,上海201306

出　　处：《广西大学学报(自然科学版)》2025年第1期38-49,共12页Journal of Guangxi University(Natural Science Edition)

基　　金：国家自然科学基金项目(71871136);教育部人文社会科学研究一般项目(23YJA630035)。

摘　　要：为了减小船舶排放监测场景下不确定因素的干扰并提高检测效率,研究无人机船舶排放监测选址路径优化问题时应考虑船舶位置不确定性对岸上基站选址的影响。针对船舶实时运动、无人机伴飞等特征建立无人机选址路径随机规划模型,设计2种选址规则并采用禁忌搜索算法求解岸上基站选址问题,进一步设计遗传算法优化无人机监测路径。数值实验结果表明,相同实验场景中,遗传算法在求解速度上具有显著优势,其求解速度是CPLEX求解的6倍;无人机数量和伴飞时长影响无人机监测任务,每增加1架无人机,无人机飞行总时间平均增加0.26 h,但可平均提前0.12 h完成监测任务;伴飞时长每增加了0.6 min,总飞行时间增加0.1~0.35 h。无人机速度提升5%,其飞行总时间可平均变化2.8%左右,随着无人机速度提升,飞行时间呈现递减趋势,其变化幅度逐渐减小。To reduce the impact of uncertainties in ship emissions monitoring scenarios and improve detection efficiency,this study considers the effect of ship position uncertainty on the location selection of onshore base stations in optimizing the drone routing and site selection for ship exhaust monitoring.To address characteristics such as real-time ship movement and drone companion flights,a stochastic programming model for drone location and routing optimization was established,two location selection rules were designed,a tabu search algorithm was applied to solve the onshore base station location selection problem,and a genetic algorithm was further designed to optimize the drone detecting routes.Numerical experiments show that in the same experimental scenarios,the genetic algorithm has a significant advantage in solving speed,achieving a speed six times faster than CPLEX.The number of drones and companion flight duration affect drone monitoring tasks.Each additional drone increases the total flight time by an average of 0.26 h but allows the detecting task to be completed an average of 0.12 h earlier.An increase of 0.6 min in companion flight duration adds 0.1 to 0.35 h to the total flight time.A 5%increase in drone speed results in an average change of approximately 2.8%in total flight time.As drone speed increases,total flight time shows a decreasing trend,and the amplitude of this change gradually diminishes.

关 键 词：无人机 船舶排放监测 选址路径问题 随机规划模型 两阶段启发式算法 

分 类 号：U698.7[交通运输工程—港口、海岸及近海工程]