支线集装箱船舶航线规划与配载协同优化  

Joint optimization in route planning and stowage for feeder container ships

作　　者：肖笛 李俊[1] 温想 赵雅洁 XIAO Di;LI Jun;WEN Xiang;ZHAO Yajie(School of Automobile and Traffic Engineering,Wuhan University of Science and Technology,Wuhan 430070,China)

机构地区：[1]武汉科技大学汽车与交通工程学院,湖北武汉430070

出　　处：《中国航海》2023年第4期54-60,共7页Navigation of China

基　　金：湖北省教育厅科学技术研究计划项目(Q20211110)。

摘　　要：针对支线集装箱船舶运输中喂给港数和靠泊条件不一的实际背景,考虑船舶容量、行驶稳性和交付时间等约束,采用两阶段分层方法研究支线集装箱船舶航线规划和配载协同优化问题。两阶段中分别以所有船舶总运营成本最小和混装堆栈数最小为目标,构建船舶航线规划和配载优化的混合整数规划(MIP)模型,结合问题特征设计粒子群算法(PSO)求解模型。结果表明:模型与算法均可实现问题求解,对于较大规模的算例,模型最长求解时间超过600 s,PSO最长求解时间为16.66 s,平均10.00 s内完成求解,表现出较好的求解性能,可为支线集装箱船舶航线规划与配载协同优化提供决策参考。For feeder container ship transportation with the characteristics of changeable feeding ports and variation of berthing conditions at ports,a two-stage method is applied to jointly optimizing route planning and cargo stowage of the feeder container ships.With the constraints of ship capacity,ship stability and cargo delivery time,a MIP(Mixed Integer Programming)model is constructed for the objective of minimizing the total operating cost of the container fleet and minimizing the number of mixed stacks.A PSO(Particle Swarm Optimization)algorithm is designed to solve the problem.Several practical cases are calculated to demonstrate the efficiency difference between direct model calculation and the PSO algorithm.For larger scale problems,the solution time for model direct calculation exceeds 600 s,while with PSO,the maximum solution time is 16.66 s and the average solution time is 10.00 s.Which can provide reference for practical optimization of feeder container ship transportation.

关 键 词：支线集装箱运输 航线规划 船舶配载 两阶段分层方法 粒子群算法 

分 类 号：U695.22[交通运输工程—港口、海岸及近海工程]