Learning-based Bi-level Multi-objective Optimization for Container Stowage Planning Problem
This study addresses the Container Stowage Planning Problem (CSPP) from a perspective of vessel-yard collaboration. A bi-level multi-objective evolutionary algorithm based on NSGA-II is proposed, in which the upper-level assigns the containers to bays and the lower-level decides specific position for each container. The algorithm employs adaptive evolutionary strategies to enhance diversity. The result of extensive experiments demonstrates the superiority of the proposed method and practical value for real-world scale CSPP in container terminal.
Authors
- Minghao Guo (ORCID: https://orcid.org/0000-0002-3680-5420)
- Yun Dong (ORCID: https://orcid.org/0000-0001-6909-7777)
Institutions
- Northeastern University (CN)
Publication Details
- Published
- 2025-06-08
- DOI
- https://doi.org/10.1109/cec65147.2025.11043072
- Primary Topic
- Maritime Ports and Logistics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China