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294. Distributionally robust optimization for the berth allocation problem under uncertainty
Invited abstract in session TA-62: Seaside Planning III, stream OR in Port Operations.
Tuesday, 8:30-10:00Room: S12 (building: 101)
Authors (first author is the speaker)
| 1. | Filipe Rodrigues
|
| ISEG, University of Lisbon | |
| 2. | Agostinho Agra
|
| Matemática, Universidade de Aveiro |
Abstract
There are several optimization problems occurring in port terminals, and the berth allocation problem (BAP) is amongst the most important ones. The BAP is highly affected by uncertainty due to many factors like weather conditions and mechanical failures. Therefore, it is crucial to take uncertainty into account when approaching BAPs. Here, we study the BAP under a distributionally robust optimization (DRO) approach. We assume that each vessel has an associated deadline to finish its operations, but delays can occur. Therefore, we aim to minimize the worst-case of the expected sum of delays of vessels with respect to a set of possible probability distributions of the handling times. The proposed model is solved by an exact algorithm enhanced with several improvement strategies that drastically reduce the associated running time. The DRO model depends on a risk-parameter that makes it possible to obtain solutions with different degrees of protection against the risk.
Extensive computational results comparing DRO, stochastic programming, and robust optimization are also reported.
Keywords
- Maritime applications
- Robust Optimization
- Stochastic Optimization
Status: accepted
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