Cooperative Optimization for Port and Shipping Line with Unpredictable Disturbance Consideration

Sun, Bo; Niu, Bohui; Xu, Haifeng; Ying, Weizhi

doi:10.1109/fskd.2018.8686901

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…The authors discretize the possible arrival times at each port to approximate the non-linear relation between fuel consumption and sailing speed. Du et al (2011) and Sun et al (2018) integrate vessel speed optimization and berth allocation by considering ships within a certain sailing distance from the port.…”

Section: Literature Reviewmentioning

confidence: 99%

An adaptive large neighborhood search heuristic for the multi-port continuous berth allocation problem

Martin-Iradi¹,

Pacino²,

Røpke³

2023

Preprint

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In this paper, we study a problem that integrates the vessel scheduling problem with the berth allocation into a collaborative problem denoted as the multi-port continuous berth allocation problem (MCBAP). This problem optimizes the berth allocation of a set of ships simultaneously in multiple ports while also considering the sailing speed of ships between ports. Due to the highly combinatorial character of the problem, exact methods struggle to scale to large-size instances, which points to exploring heuristic methods. We present a mixed-integer problem formulation for the MCBAP and introduce an adaptive large neighborhood search (ALNS) algorithm enhanced with a local search procedure to solve it. The computational results highlight the method's suitability for larger instances by providing high-quality solutions in short computational times. Practical insights indicate that the carriers' and terminal operators' operational costs are impacted in different ways by fuel prices, external ships at port, and the modeling of a continuous quay.

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Section: Literature Reviewmentioning

confidence: 99%

An adaptive large neighborhood search heuristic for the multi-port continuous berth allocation problem

Martin-Iradi¹,

Pacino²,

Røpke³

2023

Preprint

View full text Add to dashboard Cite

show abstract

Joint Voyage Planning and Onboard Energy Management of Hybrid Propulsion Ships

Wang

Liang

Aktas

et al. 2023

JMSE

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Maritime transportation decarbonization has become a crucial factor in reducing carbon emissions and mitigating climate change. As an industry that historically relies on fossil fuels, in particular, heavy fuel oil, the reinvention of the maritime transportation system is occurring at an unprecedented speed to integrate renewable and green energy, low-/zero- carbon fuels, and green infrastructure to support emission-free shipping. In this paper, a two-stage joint optimization model is proposed to optimize the voyage planning of a ship among multiple ports as well as its onboard energy management during each section of the voyage. More specifically, in the first stage, the arrival time of ships is optimized according to the mission of the ship and the electricity prices offered at each port. In the second stage, the speed of the ship, the dispatch of the onboard diesel engine, and the usage of energy storage systems (ESSs) are optimized based on emission control areas and maritime meteorological conditions. Simulation results have shown that the proposed approach would help ship operators minimize the operating cost over the whole voyage while significantly contributing to carbon emissions reduction.

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Cooperative Optimization for Port and Shipping Line with Unpredictable Disturbance Consideration

Cited by 2 publications

References 15 publications

An adaptive large neighborhood search heuristic for the multi-port continuous berth allocation problem

An adaptive large neighborhood search heuristic for the multi-port continuous berth allocation problem

Joint Voyage Planning and Onboard Energy Management of Hybrid Propulsion Ships

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