Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach
Effective cooperation between railways and seaports is crucial for enhancing the efficiency of seaport-hinterland corridors (SHC) . However, existing challenges stem from fragmented decision-making across seaports, rail operators, and inland cities, leading to asynchronous routing and scheduling, su...
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MDPI AG
2025-04-01
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| author | Yueyi Li Xiaodong Zhang |
| author_facet | Yueyi Li Xiaodong Zhang |
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| description | Effective cooperation between railways and seaports is crucial for enhancing the efficiency of seaport-hinterland corridors (SHC) . However, existing challenges stem from fragmented decision-making across seaports, rail operators, and inland cities, leading to asynchronous routing and scheduling, suboptimal service coverage, and delays. Addressing these issues requires a comprehensive approach to scheduled train service design from a network-based perspective. To tackle the challenges in SHCs, we propose a targeted networked solution that integrates multimodal coordination and resource optimization. The proposed framework is built upon a time-space-state network model, incorporating service selection, timing, and frequency decisions. Furthermore, an improved adaptive large neighborhood search (ALNS) algorithm is developed to enhance computational efficiency and solution quality. The proposed solution is applied to a representative land–sea transport corridor to assess its effectiveness. Compared to traditional operational strategies, our optimized approach yields a 7.6% reduction in transportation costs and a 56.6% decrease in average cargo collection time, highlighting the advantages of networked service coordination. The findings underscore the potential of network-based operational strategies in reducing costs and enhancing efficiency, particularly under unbalanced demand distributions. Additionally, effective demand management policies and targeted infrastructure capacity enhancements at bottleneck points may play a crucial role in practical implementations. |
| format | Article |
| id | doaj-art-5ebb0d1efd0e4e769d6eaae6ff5cd336 |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-04-01 |
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| spelling | doaj-art-5ebb0d1efd0e4e769d6eaae6ff5cd3362025-08-20T02:18:00ZengMDPI AGMathematics2227-73902025-04-01138130210.3390/math13081302Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network ApproachYueyi Li0Xiaodong Zhang1Department of Logistics Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Shangyuan Cun, Haidian District, Beijing 100044, ChinaDepartment of Logistics Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Shangyuan Cun, Haidian District, Beijing 100044, ChinaEffective cooperation between railways and seaports is crucial for enhancing the efficiency of seaport-hinterland corridors (SHC) . However, existing challenges stem from fragmented decision-making across seaports, rail operators, and inland cities, leading to asynchronous routing and scheduling, suboptimal service coverage, and delays. Addressing these issues requires a comprehensive approach to scheduled train service design from a network-based perspective. To tackle the challenges in SHCs, we propose a targeted networked solution that integrates multimodal coordination and resource optimization. The proposed framework is built upon a time-space-state network model, incorporating service selection, timing, and frequency decisions. Furthermore, an improved adaptive large neighborhood search (ALNS) algorithm is developed to enhance computational efficiency and solution quality. The proposed solution is applied to a representative land–sea transport corridor to assess its effectiveness. Compared to traditional operational strategies, our optimized approach yields a 7.6% reduction in transportation costs and a 56.6% decrease in average cargo collection time, highlighting the advantages of networked service coordination. The findings underscore the potential of network-based operational strategies in reducing costs and enhancing efficiency, particularly under unbalanced demand distributions. Additionally, effective demand management policies and targeted infrastructure capacity enhancements at bottleneck points may play a crucial role in practical implementations.https://www.mdpi.com/2227-7390/13/8/1302seaport-hinterland corridortime-space-state networkscheduled trainnetworked operationadaptive large neighborhood search |
| spellingShingle | Yueyi Li Xiaodong Zhang Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach Mathematics seaport-hinterland corridor time-space-state network scheduled train networked operation adaptive large neighborhood search |
| title | Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach |
| title_full | Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach |
| title_fullStr | Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach |
| title_full_unstemmed | Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach |
| title_short | Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach |
| title_sort | optimizing scheduled train service for seaport hinterland corridors a time space state network approach |
| topic | seaport-hinterland corridor time-space-state network scheduled train networked operation adaptive large neighborhood search |
| url | https://www.mdpi.com/2227-7390/13/8/1302 |
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