Inland Container Liner Route Stowage Planning Decision with Uncertain Container Weight

Abstract

Abstract:

The inland container liner shipping has its particularity comparing with the maritime container shipping. For the domestic trade containers, the uncertainty of weight information which is provided by the cargo owners when booking the shipping space has made the route stowage planning decision more complex. Considering the uncertain container weight, the stochastic programming model for inland container liner route stowage planning decision is built with the objective of minimizing the ship stack occupancy number over the full route. The stochastic programming model is translated into the stochastic chance-constrained programming model based on the stochastic programming theory by describing the stochastic constraints with chance constraints. The hybrid neighborhood search algorithm consisting of Monte Carlo stochastic simulation, neural network training, and neighborhood search heuristics is designed for solving the proposed model. Numerical examples show the hybrid neighborhood search algorithm has a good robustness as it can make the stowage plan to absorb the uncertainty effectively.

Key words: waterway transportation, route stowage planning decision, hybrid neighborhood search algorithm, container transportation, inland liner shipping, uncertain container weight, stochastic chance-constrained programming

摘要：

与集装箱海运相比内河集装箱班轮运输具有其独特性，同时对于内贸箱而言，货主订舱时箱重信息的不确定性导致其航线配载决策变得更加复杂.本文考虑不确定箱重影响，以最小化航线班轮堆栈占用数量为目标，构建内河集装箱班轮航线配载决策的随机规划模型.为实现求解，基于随机规划理论，采用机会约束描述随机约束，将随机规划模型转化为随机机会约束规划模型，并设计混合邻域搜索算法求解.算法由蒙特卡罗随机模拟、神经元网络训练及邻域搜索启发式3个部分组成.算例研究表明，混合邻域搜索算法的鲁棒性较好，可实现配载计划对不确定因素的有效吸收.

关键词: 水路运输, 航线配载决策, 混合邻域搜索算法, 集装箱运输, 内河班轮, 不确定箱重, 随机机会约束规划

CLC Number:

U169.6

LI Jun, ZHANG Yu, JI San-you, CHENG Zhao, MA Jie. Inland Container Liner Route Stowage Planning Decision with Uncertain Container Weight[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 208-215.

李俊，张煜，计三有，程昭，马杰. 不确定箱重下内河集装箱班轮航线配载决策[J]. 交通运输系统工程与信息, 2018, 18(2): 208-215.

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URL: http://www.tseit.org.cn/EN/abstract/abstract19612.shtml

http://www.tseit.org.cn/EN/Y2018/V18/I2/208

References

[1] AZEVEDO A, RIBEIRO C, SENA G, et al. Solving the 3D container ship loading planning problem by representation by rules and meta-heuristics[J]. International Journal of Data Analysis Techniques and Strategies, 2014(6): 228-260.

[2] DING D, CHOU M C. Stowage planning for container ship: A heuristic algorithm to reduce the number of shifts[J]. European Journal of Operational Research, 2015(246): 242-249.

[3] AMBROSINO D, PAOLUCCI M, SCIOMACHENA A. A MIP heuristic for multi-port stowage planning[J]. Transportation Research Procedia, 2015(10): 725-734.

[4] 祝慧灵, 计明军. 集装箱船舶全航线配载优化模型与改进遗传算法[J]. 交通运输工程学报, 2014, 14(5): 59-67. [ZHU H L, JI M J. Optimal model and improved genetic algorithm of containership stowage on full route[J]. Journal of Traffic and Transportation Engineering, 2014, 14(5): 59-67.]

[5] AMBROSINO D, PAOLUCCI M, SCIOMACHENA A. Computational evaluation of a MIP model for multi-port stowage planning problems[J]. Soft Computing, 2017 (21): 1753-1763.

[6] ARAÚJO E J, CHAVES A A, NETO L L S, et al. Pareto clustering search applied for 3D container ship loading plan problem[J]. Expert Systems with Applications, 2016 (44): 50-57.

[7] DONG J X, LEE C H, SONG D P. Joint service capacity planning and dynamic container routing in shipping network with uncertain demands[J]. Transportation Research Part B, 2015(78): 404-421.

[8] 杨华龙, 刘迪, 夏秋. 集装箱班轮多港挂靠循环航次舱位分配[J]. 重庆交通大学学报(自然科学版), 2012, 31 (6): 1248-1251. [YANG H L, LIU D, XIA Q. Slot allocation of container liner in multi-port call cycle voyage[J]. Journal of Chongqing Jiaotong University (Natural Science), 2012, 31(6): 1248-1251.]

[9] 郭子坚, 许松乔, 王文渊, 等. 集装箱港口堆场箱位数的二阶段随机规划方法[J]. 哈尔滨工程大学学报, 2013, 34(12): 1520-1523. [GUO Z J, XU S Q, WANG W Y, et al. The two-stage stochastic programming method for determining the number of flat containers in the port yard[J]. Journal of Harbin Engineering University, 2013, 34(12): 1520-1523.]

[10] ZHAO R Q, LIU B D. Stochastic programming models for general redundancy optimization problems[J]. IEEE Transaction on Reliability, 2003, 52(2): 181-191.

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