An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

Zhao, Yuzhe; Zhou, Jingmiao; Yu-jun, Fan; Kuang, Haibo

doi:10.1109/access.2019.2962210

Cited by 8 publications

(6 citation statements)

References 47 publications

(45 reference statements)

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“…The data from the above three sources need to be consistent in time and space to form a complete dataset called "ship AIS-marine meteorology-sea air pollution" [27]. The original datasets have three common attributes: time (Time), longitude (LON), and latitude (LAT).…”

Section: Data Fusionmentioning

confidence: 99%

A Big-Data-Based Experimental Platform for Green Shipping Monitoring and Its Teaching Application

et al. 2023

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The construction of New Business Studies (NBS) in China and big data technology offer an opportunity for teaching reform. Based on the existing teaching resources, professional knowledge, data, and technology, we monitored the dynamics and checked the statistics of air pollutant emissions from ships in global waters. Various techniques of big data analysis and methods of artificial intelligence were employed, including data collection, data fusion, feature analysis, deep learning network, and system testing. Specifically, the scenario of green shipping monitoring was reproduced by virtual reality; experimental learning was carried out, involving five experimental methods, eight experimental steps, and ten interactive operations; and the results of the experimental learning were assessed. In this way, the students had a better cognition of datasets, a deeper understanding of data correlation, and an improved mastery of interactive operations. In addition, the students varied in terms of learning performance, experimental participation, and active performance inspired by individual thinking. Overall, the students were satisfied with the quality of experimental learning.

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Section: Data Fusionmentioning

confidence: 99%

A Big-Data-Based Experimental Platform for Green Shipping Monitoring and Its Teaching Application

et al. 2023

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“…Different speed optimization solutions have been implemented in the literature to define the right speed when performing maritime transportation operations. Zhao et al [52] and Yuzhe et al [53] proposed a novel approach for sailing speed optimization that uses a solver based on a genetic algorithm to balance delivery delays, sulfur oxide emissions, and fuel consumption. Instead, Wong et al [54] developed two continuous utility-based decision support models for ship liners sustainability that need to determine the optimal speed for slow steaming operations.…”

Section: Speed Optimization Problemsmentioning

confidence: 99%

Smart Steaming: A New Flexible Paradigm for Synchromodal Logistics

2021

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Slow steaming, i.e., the possibility to ship vessels at a significantly slower speed than their nominal one, has been widely studied and implemented to improve the sustainability of long-haul supply chains. However, to create an efficient symbiosis with the paradigm of synchromodality, an evolution of slow steaming called smart steaming is introduced. Smart steaming is about defining a medium speed execution of shipping movements and the real-time adjustment (acceleration and deceleration) of traveling speeds to pursue the entire logistic system’s overall efficiency and sustainability. For instance, congestion in handling facilities (intermodal hubs, ports, and rail stations) is often caused by the common wish to arrive as soon as possible. Therefore, smart steaming would help avoid bottlenecks, allowing better synchronization and decreasing waiting time at ports or handling facilities. This work aims to discuss the strict relationships between smart steaming and synchromodality and show the potential impact of moving from slow steaming to smart steaming in terms of sustainability and efficiency. Moreover, we will propose an analysis considering the pros, cons, opportunities, and risks of managing operations under this new policy.

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“…Green ports and maritime logistics are relatively new with rapid growth since 2006 [14]. Although most researches on green ports focus on ECAs policy and its impact [15]- [18], there is limited research on the sustainable port technologies [19], [20]. Tseng and Pilcher [21] studied the challenges of introducing SP in Kaohsiung port using qualitative and quantitative methods with stakeholders.…”

Section: A Green Portsmentioning

confidence: 99%

Using System Dynamics and Game Model to Estimate Optimal Subsidy in Shore Power Technology

Kuang

2020

IEEE Access

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To cope with severe environmental problems, the government has implemented strict emission control policies, and promoted the use of technology such as shore power (SP) in the form of subsidies. The SP providers of the shipping lines like the ports provide better SP services to shipping lines by improving its reliability, such as safety and standardization. This paper examines a two-echelon maritime supply chain consisting of a port and a shipping line under government green subsidy and explores the subsidy mechanism and its impact. The optimal government subsidy intensity and subsidy reduction point are confirmed using game theory. The system dynamics (SD) method is used to analyze the influence and evolution of practical problems such as government subsidy efficiency, information asymmetry, and inconsistent decision-making periods under multiple games utilizing the optimal response function. The paper shows that both shipper SP preference and decision period affect the SP reliability. When the shipper's preference is high, the actual shipper's subsidies and government subsidies are inefficient. Information asymmetry borne by ports and shipping line causes considerable fluctuations in the game and does not affect the actual subsidies received by shippers. Also, shipping line downstream of the supply chain are more affected by it. This paper offers insight for the government to formulate subsidy policies in the maritime supply chain.

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An Expected Utility-Based Optimization of Slow Steaming in Sulphur Emission Control Areas by Applying Big Data Analytics

Cited by 8 publications

References 47 publications

A Big-Data-Based Experimental Platform for Green Shipping Monitoring and Its Teaching Application

A Big-Data-Based Experimental Platform for Green Shipping Monitoring and Its Teaching Application

Smart Steaming: A New Flexible Paradigm for Synchromodal Logistics

Using System Dynamics and Game Model to Estimate Optimal Subsidy in Shore Power Technology

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