Speed optimization and bunkering in liner shipping in the presence of uncertain service times and time windows at ports

DOI10.1016/j.ejor.2016.10.002zbMath1394.90076OpenAlexW2528754946MaRDI QIDQ1751781

Xianqiang Yang

Publication date: 25 May 2018

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2016.10.002

zbMATH Keywords

transportationdynamic programmingOR in maritime industryfuel cost

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Transportation, logistics and supply chain management (90B06) Deterministic scheduling theory in operations research (90B35) Case-oriented studies in operations research (90B90) Dynamic programming (90C39)

Related Items (9)

A decision support system for vessel speed decision in maritime logistics using weather archive big data ⋮ Tug scheduling for hinterland barge transport: a branch-and-price approach ⋮ Bunkering and information decisions in the sea cargo service industry based on uncertain spot price ⋮ Coordinating vessel recovery actions: analysis of disruption management in a liner shipping service ⋮ Uncertainty in maritime ship routing and scheduling: a literature review ⋮ Integrated planning of ship deployment, service schedule and container routing ⋮ Vessel velocity decisions in inland waterway transportation under uncertainty ⋮ Bunker fuel cost and freight revenue optimization for a single liner shipping service ⋮ Bunkering policies for a fuel bunker management problem for liner shipping networks

Cites Work

• Bunkering decisions for a shipping liner in an uncertain environment with service contract
• Liner shipping network design with deadlines
• The theory and practice of revenue management
• The vessel schedule recovery problem (VSRP) -- a MIP model for handling disruptions in liner shipping
• Ship routing and scheduling in the new millennium
• Dynamic determination of vessel speed and selection of bunkering ports for liner shipping under stochastic environment
• Analysis of an exact algorithm for the vessel speed optimization problem
• Reducing fuel emissions by optimizing speed on shipping routes

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