Synchronized scheduling model for container terminals using simulated double-cycling strategy

Ahmed, Essmeil; El-Abbasy, Mohammed S.; Zayed, Tarek; Alfalah, Ghasan; Alkass, Sabah

doi:10.1016/j.cie.2021.107118

Cited by 27 publications

(7 citation statements)

References 61 publications

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“…Hu Compared to AGVs under central control unit, AMRs can communicate and negotiate independently with other resources such as machines and systems, thus decentralize the decision-making process [15]. Ahmed et al proposed a double-cycling strategy to minimize the number of empty travel trips of yard trucks, and verified the enhanced efficiency of the proposed strategy by comparing the simulation models of standard single-cycling and double-cycling [16].…”

Section: A Optimization Of Horizontal Transport In Actsmentioning

confidence: 99%

Study on Distributed Consistent Cooperative Control of Multi-ART in Automated Container Terminals

Yang

Tang

et al. 2022

IEEE Access

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In order to address the congestion problem of vehicles in quay of automated container terminal with parallel layout and side-loading operations, the study regards the terminal operation system as a multiagent system (MAS), and proposes a dynamic cooperative speed control schema of multi-ART(Artificial Intelligence Robot of Transportation, ) for the purpose of smart and distributed traffic control of container terminals. Via the real-time data interchange and message passing with ART group, the individual ART implements the collaborative speed regulation with the combination of the dynamic speed regulation strategy, so as to adjust the sequence of ARTs arriving at the quay which can decrease the waiting time of ARTs at the quay. Considering the consistency problem of individual and group agent among the dynamic speed regulation of ARTs, a novel distributed consensus protocol is established to assure that the individual status of ART will tend to converge basically during the collaborative speed regulation process, and the convergence of system can be guaranteed. Based on the case of automated container terminal of Tianjin Port, the paper establishes a multi-agent based simulation model, and simulates the decision-making process, and validates the effectiveness of mentioned model and strategy. The results demonstrate that the strategy can decrease the waiting time of ARTs under uncertainty environment of port and improve the operation efficiency of system.

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Section: A Optimization Of Horizontal Transport In Actsmentioning

confidence: 99%

Study on Distributed Consistent Cooperative Control of Multi-ART in Automated Container Terminals

Yang

Tang

et al. 2022

IEEE Access

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“…UNCTAD [48] reports a median time spent in each port on single port calls of 23.5 h for container ships. Container handling operations depend on the functionality of each port, and Ahmed et al [66] report an overall productivity rate for loading and unloading cargo on a quay crane of 61.68 TEUs/. Obviously, the longer the vessel the more cranes that need to be employed.…”

Section: Appendix a Port Dutiesmentioning

confidence: 99%

Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System

Goicoechea

Abadie

2021

Energies

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Slow steaming is an operational measure in ocean-going vessels sailing at slow speeds. It can help climate mitigation efforts by cutting down marine fuel consumption and consequently reducing CO2 and other Greenhouse Gas Emissions (GHG). Due to climate change both the European Union (EU) and the International Maritime Organization (IMO) are analysing the inclusion of international shipping in the EU Emissions Trading System (ETS) in the near future or alternatively implementing a carbon tax. The paper proposes a methodology to decide the optimal speed of a vessel taking into account its characteristics and the factors that determine its economic results. The calculated cash flow can be used in valuation models. The methodology is applied for a case study for any container ship in a range from 2000 to 20,000 Twenty-foot Equivalent Units (TEU) on a leg of a round trip from Shanghai to Rotterdam. We calculate how speed reduction, CO2 emissions and ship owner’s earnings per year may vary between a business-as-usual scenario and a scenario in which shipping is included in the ETS. The analysis reveals that the optimal speed varies with the size of the vessel and depends on several variables such as marine fuel prices, cargo freight rates and other voyage costs. Results show that the highest optimal speed is in the range of 5500–13,000 TEUs whether or not the ETS is applied. As the number of TEUs transported in a vessel increases emissions per TEU decrease. In an established freight rate market, the optimal speed fluctuates by 1.8 knots. Finally, the medium- and long-term expectations for slow steaming are analysed based on future market prices.

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“…By 2020, global container throughput reached approximately 800 million TEU, an increase of almost 50% compared to 542 million TEU in 2010. With the development of larger and faster ships, the container throughput is continually increasing, which makes port logistics even more complex [2]. According to UNCTAD [3], the proportion of maritime cargo carried by mega-container ships worldwide has increased from an initial 6% in 2011 to almost 40% in 2021.…”

Section: Introduction 1background and Motivationmentioning

confidence: 99%

Bi-Objective Integrated Scheduling of Quay Cranes and Automated Guided Vehicles

Duan

Ren

et al. 2023

JMSE

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Operational efficiency is one of the key performance indicators of a port’s service level. In the process of making scheduling plans for container terminals, different types of equipment are usually scheduled separately. The interaction between quay cranes (QCs) and automated guided vehicles (AGVs) is neglected, which results in low operational efficiency. This research explores the integrated scheduling problem of QCs and AGVs. Firstly, a multi-objective mixed integer programming model (MOMIP) is conducted, with the aim of minimizing the makespan of vessels and the unladen time of AGVs. Then, embedded with a new heuristic method, the non-dominated sorting genetic algorithm-II (NSGA-II) is designed for the scheduling problem. The heuristic method includes two parts: a bay-based QC allocation strategy and a container-based QC-AGV scheduling strategy. Finally, in order to test the performance of the proposed algorithm, differently sized benchmark tests are performed, and the results are compared to the multi-objective particle swarm optimization algorithm (MOPSO) and the weighted-sum method. The computational results indicate that the proposed algorithm can effectively solve the multi-objective integrated scheduling problem of QCs and AGVs. For large-scale problems, the NSGA-II algorithm has better performance and more obvious advantages compared to others. The proposed method has the capability of providing a theoretical reference for the QC and AGV scheduling of container terminals.

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Synchronized scheduling model for container terminals using simulated double-cycling strategy

Cited by 27 publications

References 61 publications

Study on Distributed Consistent Cooperative Control of Multi-ART in Automated Container Terminals

Study on Distributed Consistent Cooperative Control of Multi-ART in Automated Container Terminals

Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System

Bi-Objective Integrated Scheduling of Quay Cranes and Automated Guided Vehicles

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