交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (1): 11-23.DOI: 10.16097/j.cnki.1009-6744.2026.01.002

• 综合交通运输体系 • 上一篇    下一篇

考虑海峡交通风险时空差异的航运公司船队路径优化

王杰1,王兴浩1,梁金鹏*1,高俊2   

  1. 1. 大连海事大学,交通运输工程学院,辽宁大连116026;2.辽宁对外经贸学院,管理学院,辽宁大连116052
  • 收稿日期:2025-07-11 修回日期:2025-10-06 接受日期:2025-10-27 出版日期:2026-02-25 发布日期:2026-02-13
  • 作者简介:王杰(1962—),男,辽宁大连人,教授,博士。
  • 基金资助:
    国家社科重大研究专项项目(18VHQ005)。

Fleet Route Optimization of Shipping Companies Under Spatiotemporal Variations in Strait Traffic Risk

WANG Jie1, WANG Xinghao1, LIANG Jinpeng*1, GAO Jun2   

  1. 1. College of Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China; 2. School of Management, Liaoning University of International Business and Economics, Dalian 116052, Liaoning, China
  • Received:2025-07-11 Revised:2025-10-06 Accepted:2025-10-27 Online:2026-02-25 Published:2026-02-13
  • Supported by:
    The Key Project of National Social Science Fund of China (18VHQ005)。

摘要: 海峡航道作为船舶运输的重要通道,据国际海事组织统计,其交通事故发生率明显高于其他水域,且呈现显著的时空分布特征。本文针对船舶交通风险的时空差异性特点,综合运用船舶自动识别系统(Automatic Identification System, AIS)数据,融合物元可拓理论与栅格法,构建海峡航道动态风险量化评估体系。在此基础上,以船队运营收益最大化为目标,以总航行风险控制为约束条件,建立混合整数规划模型。该模型能够优化船舶航速配置,运输路径选择,特别是海峡航道的精细化路径规划,并采用Gurobi求解器进行高效求解。基于某航运公司原油运输实际数据的案例,分析验证了模型的有效性:通过动态航速调整和替代路径选择策略,能够有效规避高风险时段和海域;风险阈值与船队总运营收益呈正相关关系;货物运输延误惩罚系数从0增至5%时,总运营收益降幅达7.04%,而从5%增至30%时,降幅仅为3.54%,呈现边际递减效应;低风险阈值条件下,系统对运输需求波动的敏感性相应降低;运输价格每提升5%,总运营收益平均增长率约为5.5%。研究成果可为航运企业制定基于风险偏好的海峡通航策略和运营决策提供科学依据和优化方案。

关键词: 水路运输, 路径优化, 物元可拓理论, 船舶交通风险, AIS, 风险时空差异

Abstract: Maritime cargo transportation through strait waterways faces elevated accident risks, with incidents exhibiting distinct spatiotemporal clustering according to the statistics from the International Maritime Organization. This study addresses spatiotemporal risk heterogeneity by developing an integrated assessment and optimization framework. Based on the data from the Automatic Identification System (AIS), this paper quantifies the dynamic risk profiles across strait waterways at various temporal scales with grid-based analysis and matter-element extension theory. A mixed-integer programming model was formulated with the aim of maximizing fleet profitability subject to aggregate risk constraints. The model simultaneously optimizes vessel speeds, route selection, and precise navigation paths through straits, and uses the Gurobi solver to solve efficiently. Empirical validation using the crude oil transportation data from a major shipping company reveals the key insights as follows: dynamic speed adjustment and adaptive routing effectively mitigate exposure to high-risk zones; fleet revenue increases monotonically with the relaxation of risk threshold; delay penalties exhibit non-linear impacts, with initial implementation (0~5%) reducing revenue by 7.04%, while subsequent increases (5%~30%) yield only 3.54% additional reduction; lower risk thresholds demonstrate reduced sensitivity to demand volatility; and price elasticity shows near-proportional relationships, with 5% price increases generating approximately 5.5% revenue growth. The findings provide some optimization recommendations for shipping companies based on their risk preferences and practical demands for navigating through straits.

Key words: waterway transportation, route optimization, matter-element extension theory, vessel traffic risk, Automatic Identification System (AIS), spatiotemporal risk variations

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