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http://hdl.handle.net/10397/88423
| Title: | Route and speed optimization for liner ships under emission control policies | Authors: | Zhen, L Hu, Z Yan, R Zhuge, D Wang, S |
Issue Date: | Jan-2020 | Source: | Transportation research. Part C, Emerging technologies, Jan. 2020, v. 110, p. 330-345 | Abstract: | Pollutants such as nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matters (PM) generated by shipping industry are increasing in recent years. In order to control the ship emission pollution, the International Maritime Organization (IMO) has established the Emission Control Areas (ECAs). In the fierce competition of the shipping market, liner shipping companies are looking for strategies to maintain their core competencies under the emission control policy. To achieve this goal, this paper first proposes a bi-objective mixed integer linear programming model, aiming to optimize sailing routes and speeds within and outside the ECA while minimizing the total fuel cost and SO2 emissions. Then, a new algorithm is developed to solve the proposed model by combining the two-stage iterative algorithm and fuzzy logic method based on ∊-constraint. Finally, this paper compares and analyzes the navigation plan of a real sailing route considering and not considering the effects of ECA. Some experiments are conducted to analyze the effects of fuel cost, decision makers, and ECA boundaries on the total fuel cost and SO2 emissions. The results indicate that the proposed model and algorithm can contribute to save fuel cost and reduce SO2 emissions under the ECA policy and provide different Pareto optimal solutions. Thus, the effectiveness of the model and the efficiency of the algorithm are validated. © 2019 Elsevier Ltd | Keywords: | Bi-objective programming Emission Control Area (ECA) Route optimization Sailing speed optimization Two-stage iterative algorithm |
Publisher: | Pergamon Press | Journal: | Transportation research. Part C, Emerging technologies | ISSN: | 0968-090X | DOI: | 10.1016/j.trc.2019.11.004 | Rights: | © 2019 Elsevier Ltd. All rights reserved. This is the preprint version of a work that was accepted for publication in Transportation Research Part C: Emerging Technologies. A definitive version was subsequently published in Transportation Research Part C: Emerging Technologies, Volume 110, January 2020, Pages 330-345, https://doi.org/10.1016/j.trc.2019.11.004 |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| a0502-n02.pdf | Preprint version | 2.35 MB | Adobe PDF | View/Open |
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