2015
DOI: 10.1080/00207179.2015.1043350
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Energy-efficient container handling using hybrid model predictive control

Abstract: The performance of container terminals needs to be improved to adapt the growth of containers while maintaining sustainability. This paper provides a methodology for determining the trajectory of three key interacting machines for carrying out the so-called bay handling task, involving transporting containers between a vessel and the stacking area in an automated container terminal. The behaviours of the interacting machines are modelled as a collection of interconnected hybrid systems. Hybrid model predictive… Show more

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Cited by 10 publications
(5 citation statements)
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References 19 publications
(19 reference statements)
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“…MPC updates decision-making in response to real-time information over a given horizon. It has wide applicability in freight transportation systems (18)(19)(20). For perishable goods logistics, MPC also has great potential in handling the decision-making process, in which quality of goods and environmental factors (such as temperature) can change rapidly.…”
Section: Literature Reviewmentioning
confidence: 99%
“…MPC updates decision-making in response to real-time information over a given horizon. It has wide applicability in freight transportation systems (18)(19)(20). For perishable goods logistics, MPC also has great potential in handling the decision-making process, in which quality of goods and environmental factors (such as temperature) can change rapidly.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The main feature of MPC is the use of the rolling optimization strategy which can make up for the disturbances caused by uncertainties of the continuously varying parameters. Due to these advantages, it has been widely used in maritime transportation such as container handling and optimization control of waterborne AGVs (Xin et al, 2015;Zheng et al, 2016). MPC can also be used to deal with the dynamical collaborative optimization problem of sailing route and speed that considers the uncertainties and continuously time-varying characteristics of the environmental and operational conditions.…”
Section: Introductionmentioning
confidence: 99%
“…In support of this approach on the dynamic optimization method considering multiple time-varying influencing factors, we develop a bi-level optimization model incorporating a high-level optimization model for operational decision-making and a low-level dynamic optimization model for energy consumption. For the dynamic optimization and control problem, the model predictive control (MPC) has attracted extensive research, because of its better dynamic control performance and the ability of compensating for disturbances caused by dynamic factors (Negenborn et al, 2008;Xin et al, 2015;Zheng et al, 2016;Liu et al, 2015). In the practical operation, it is difficult to communicate effectively between ships and to achieve the centralized control from the shipping company.…”
Section: Introductionmentioning
confidence: 99%