Optimization of empty container repositioning considering carbon tax
Maritime transport has been a facilitator of international trade for decades, among which container shipping has contributed a major part. Although the growth of maritime trade stalled due to the breakout of the COVID-19 pandemic, it has been steadily recovering as the pandemic eases. However, due...
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2022
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sg-ntu-dr.10356-1581442022-06-03T22:34:57Z Optimization of empty container repositioning considering carbon tax Wang, Jinyue Wang Zhiwei School of Civil and Environmental Engineering WangZhiwei@ntu.edu.sg Engineering::Civil engineering Maritime transport has been a facilitator of international trade for decades, among which container shipping has contributed a major part. Although the growth of maritime trade stalled due to the breakout of the COVID-19 pandemic, it has been steadily recovering as the pandemic eases. However, due to the imbalanced inter-regional trade recovery rate, the container segment is suffering from seriously asymmetric cargo flow. The importing countries are crowded with empty containers while the exporting countries are, on the contrary, lacking empty containers. An efficient empty container reposition scheme is believed to be a helpful solution. But the repositioning is expensive, and companies do not reap economic benefit directly therefrom. Moreover, the new carbon pricing measures might have an impact on repositioning costs as well. In order to optimize the cost-efficiency of the repositioning process, this project is to build a linear programming model with the consideration of carbon pricing together with bunker and handling costs in order to minimize the empty container repositioning cost. Bachelor of Science (Maritime Studies) 2022-05-30T08:48:55Z 2022-05-30T08:48:55Z 2022 Final Year Project (FYP) Wang, J. (2022). Optimization of empty container repositioning considering carbon tax. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158144 https://hdl.handle.net/10356/158144 en MS-30 application/pdf Nanyang Technological University |
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Engineering::Civil engineering Wang, Jinyue Optimization of empty container repositioning considering carbon tax |
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Maritime transport has been a facilitator of international trade for decades, among which container shipping has contributed a major part. Although the growth of maritime trade stalled due to the breakout of the COVID-19 pandemic, it has been steadily recovering as the pandemic eases. However, due to the imbalanced inter-regional trade recovery rate, the container segment is suffering from seriously asymmetric cargo flow. The importing countries are crowded with empty containers while the exporting countries are, on the contrary, lacking empty containers. An efficient empty container reposition scheme is believed to be a helpful solution. But the repositioning is expensive, and companies do not reap economic benefit directly therefrom. Moreover, the new carbon pricing measures might have an impact on repositioning costs as well. In order to optimize the cost-efficiency of the repositioning process, this project is to build a linear programming model with the consideration of carbon pricing together with bunker and handling costs in order to minimize the empty container repositioning cost. |
author2 |
Wang Zhiwei |
author_facet |
Wang Zhiwei Wang, Jinyue |
format |
Final Year Project |
author |
Wang, Jinyue |
author_sort |
Wang, Jinyue |
title |
Optimization of empty container repositioning considering carbon tax |
title_short |
Optimization of empty container repositioning considering carbon tax |
title_full |
Optimization of empty container repositioning considering carbon tax |
title_fullStr |
Optimization of empty container repositioning considering carbon tax |
title_full_unstemmed |
Optimization of empty container repositioning considering carbon tax |
title_sort |
optimization of empty container repositioning considering carbon tax |
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Nanyang Technological University |
publishDate |
2022 |
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https://hdl.handle.net/10356/158144 |
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1735491220921122816 |