Vessel scheduling under different tugboat allocation policies. (March 2023)

• Record Type: Journal Article
• Authors: Abou Kasm, Omar; Diabat, Ali; Ozbay, Kaan
• Is Part Of: Computers & industrial engineering. Volume 177(2023)
• Publication Date: 2023-03
• Subjects: Vessel scheduling -- Channel restrictions -- Tugboat allocation -- Policy decision making -- Mixed integer programming -- Case study; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108902
• Languages: English
• ISSNs: 0360-8352

Abstract

Abstract: Vessel scheduling in seaports correlates with achieving better resource utilization and higher customer satisfaction. It has received limited attention when considered under channel restrictions, especially when berthing resources are accounted for. Tugboats play an essential role while berthing and unberthing vessels and tugboat allocation policies can differ from one port to another. In this work, we introduce mixed integer programs to model vessel scheduling under channel restrictions and different tugboat allocation policies. We then introduce bounds and enhancements on the proposed models; the enhancements are based on constructive greedy heuristics that run in polynomial time. Additionally, we discuss how the proposed mixed integer programs can be embedded alongside simulation and forecasting tools in larger frameworks that aid in policy decision making. Next, a case study is conducted to compare three tugboat allocation policies; two of which are used in practice, adapted from Ras el Khaimah Port and Maritime and Port Authority of Singapore, and one is adapted from the literature. The results indicate that identifying a better policy is case-specific where it depends on expected vessel lengths and available resources, among other factors. Finally, we show that optimizing tugboat allocations is important even if the vessel sequence is predetermined. Highlights: We consider vessel scheduling under different tugboat allocation policies. Introduce mixed integer program (MIP) variations to capture different allocation policies. Present bounds and enhancements, based on constructive greedy heuristics, on the proposed MIPs. Embed the MIPs in a framework for policy decision making. Present a case study on tugboat allocation policy comparisons.