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

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

This paper analyses the operator's risk-based decision (RBD) company for slow steaming, and creates a sailing speed optimization model for slow steaming (SSOM-SS), aiming to balance the expected utility-based objectives (EUO) of fuel consumption, SOx emissions and delivery delay. Considering th...

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Bibliographic Details
Main Authors: Yuzhe Zhao, Jingmiao Zhou, Yujun Fan, Haibo Kuang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Big data analytics (BDA)
slow steaming
sailing speed optimization
fuel consumption
genetic algorithm (GA)
risk aversion
Online Access:https://ieeexplore.ieee.org/document/8943336/

Internet

https://ieeexplore.ieee.org/document/8943336/

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