交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (3): 114-123.DOI: 10.16097/j.cnki.1009-6744.2026.03.011

• 综合交通运输体系 • 上一篇    下一篇

上海港集装箱内陆集疏运网络韧性评估

赵楠a ,崔浩淼b ,钟发春b ,郁斢兰*a   

  1. 上海海事大学,a.上海国际航运研究中心;b.交通运输学院,上海201306
  • 收稿日期:2026-01-14 修回日期:2026-03-23 接受日期:2026-04-16 出版日期:2026-06-25 发布日期:2026-06-22
  • 作者简介:赵楠(1986—),女,山西忻州人,研究员,博士。
  • 基金资助:
    中国社会科学院上海市人民政府上海研究院项目 (2025jb006);上海市人民政府决策咨询研究重大课题 (2025-A-07)。

Resilience Assessment of Shanghai Port's Containerized Inland Hinterland Network

ZHAO Nana, CUI Haomiaob, ZHONG Fachunb,YU Tiaolan*a   

  1. a. Shanghai International Shipping Institute; b. College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
  • Received:2026-01-14 Revised:2026-03-23 Accepted:2026-04-16 Online:2026-06-25 Published:2026-06-22
  • Supported by:
    The Project of Shanghai Academy,Chinese Academy of Social Sciences and Shanghai Municipal People's Government (2025jb006);The Major Project of Decision-Making Consultation of the Shanghai Municipal People's Government (2025-A-07)。

摘要: 港口内陆集疏运网络由港口、铁路/公路集装箱站等多类节点耦合构成,重大扰动会造成局部连通性下降并在运输组织重分配下引发功能性连锁退化。为量化该类网络在重大扰动下的韧性水平,本文提出韧性四边形模型,将韧性过程解构为抵御-吸收-适应-恢复这4个阶段,并基于Space-P法构建上海港内陆集疏运无向加权网络,涵盖253个节点(港口、铁路/公路集装箱站)与1067条连边。在此基础上,设计并仿真4类节点攻击-恢复策略(随机/蓄意攻击×随机/蓄意恢复),评估不同扰动与恢复规则下的网络韧性差异。结果表明:在“随机攻击+蓄意恢复”策略下网络韧性最优(网络韧性度量值 NT =0.16,网络韧性损失值SNT=172.50),而“蓄意攻击+随机恢复”策略下韧性最差(NT =0.27,SNT=257.50);子网络中,公路网络下降速率最小,恢复速度最快,韧性排序为公路>水路>铁路;在移除集疏运网络中的全部水路节点、铁路节点和公路节点后,剩余集疏运网络性能值分别为0.57、0.91和0.37,子网络在集疏运网络中的重要性为公路>水路>铁路。

关键词: 综合交通运输, 网络韧性评估, 复杂网络理论, 集装箱内陆集疏运网络

Abstract: The port-hinterland intermodal transport network consists of multiple types of coupled nodes, including ports and rail/ road container terminals. Major disruptions can reduce local connectivity and, through the reallocation of transport operations, trigger cascading functional degradation. To quantify the resilience of multimodal container networks under major disruptions, this paper proposes a "resilience quadrilateral" model that decomposes the resilience process into four sequential phases, including resist, absorb, adapt, and recover. Using the Space-P approach, this study built an undirected weighted hinterland network for the Port of Shanghai which encompasses 253 nodes (port terminals, rail container yards, and road container depots) and 1 067 links. On this basis, four node attack-recovery strategies are designed and simulated to evaluate differences in network resilience under different disruption and recovery rules. The results reveal that (1) the overall network attains its highest resilience under the "random attack + prioritized recovery" regime ( NT = 0.16, SNT = 172.50) and has its lowest resilience under "targeted attack + random recovery" ( NT = 0.27, SNT = 257.50); (2) at the sub-network level, the road network shows the smallest performance decline rate and the fastest recovery, the resilience of road is better than inland-waterway, and inland-waterway has better resilience than rail; (3) after removing all waterway nodes, all rail nodes, and all road nodes, the remaining network performance values are respectively 0.57, 0.91, and 0.37, indicating that the sub-network importance ranks as road, then waterway, then rail.

Key words: integrated transportation, network resilience assessment, complex network theory, port-hinterland container feeder network

中图分类号: