Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/116274
| Title: | Integrated cruise fleet deployment and itinerary scheduling problem : an enhanced Benders decomposition approach | Authors: | Yang, Y Zhang, S Wang, S |
Issue Date: | Nov-2025 | Source: | Transportation research. Part B, Methodological, Nov. 2025, v. 201, 103321 | Abstract: | With the growing popularity of cruise tourism, the issue of comprehensive and precise cruise management is emphasized by the industrial field, which demands effective strategies in both tactical-level cruise deployment and operational-level itinerary scheduling. This rising concern and the expectation of integrated decision, however, increase the complexity of the problem and the difficulty of optimization. This paper provides a cohesive framework and scalable algorithms for the integrated cruise fleet deployment and itinerary scheduling problem. First, to address this problem, we propose an integer programming model based on a time-expanded network that captures the movement dynamics of cruises over a planning horizon. Several problem-specific reformulations including cumulative-flow-based variables and route-based time-expanded network representation are introduced, based on which, we prove that the itinerary scheduling problem is totally unimodular and the integer variables can be relaxed. Second, we introduce a tailored Benders decomposition approach augmented by the simultaneous Magnanti–Wong method, where a valid and pre-obtainable Magnanti–Wong bound is designed, yielding Pareto-optimal cuts in small computation time in each iteration. Finally, we validate our approach using extensive numerical experiments on both simulation instances and a real case study. The results demonstrate the effectiveness of our integrated solving scheme and the practical applicability of our advanced decomposition method, marking a significant advancement in the field of cruise fleet management. | Keywords: | Benders decomposition Cruise deployment Integrated optimization Itinerary scheduling Simultaneous Magnanti–Wong method Totally unimodular |
Journal: | Transportation research. Part B, Methodological | DOI: | 10.1016/j.trb.2025.103321 |
| Appears in Collections: | Journal/Magazine Article |
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



