Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
In response to growing environmental concerns and regulatory pressures, reducing carbon emissions in maritime transport has become a priority. Shipping companies face the challenge of balancing profitability objectives with the imperative to minimize their environmental footprint. This study address...
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| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/4/752 |
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| author | Haiying Yang Feiyang Ren Jingbo Yin Siqi Wang Rafi Ullah Khan |
| author_facet | Haiying Yang Feiyang Ren Jingbo Yin Siqi Wang Rafi Ullah Khan |
| author_sort | Haiying Yang |
| collection | DOAJ |
| description | In response to growing environmental concerns and regulatory pressures, reducing carbon emissions in maritime transport has become a priority. Shipping companies face the challenge of balancing profitability objectives with the imperative to minimize their environmental footprint. This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. The Gale–Shapley algorithm is employed to achieve stable vessel–cargo matching, and the genetic algorithm is adopted for iterative optimization. This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. The findings provide valuable theoretical guidance for shipping companies navigating increasingly stringent CII regulations. |
| format | Article |
| id | doaj-art-351f0d02f9534fbfa77a93eee1d6e2cf |
| institution | OA Journals |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-351f0d02f9534fbfa77a93eee1d6e2cf2025-08-20T02:28:23ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-04-0113475210.3390/jmse13040752Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) OptimizationHaiying Yang0Feiyang Ren1Jingbo Yin2Siqi Wang3Rafi Ullah Khan4State Key Laboratory of Ocean Engineering, Department of Transportation Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaCOSCO Shipping Technology Co., Ltd., Shanghai 200135, ChinaState Key Laboratory of Ocean Engineering, Department of Transportation Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaState Key Laboratory of Ocean Engineering, Department of Transportation Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaState Key Laboratory of Ocean Engineering, Department of Transportation Engineering, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaIn response to growing environmental concerns and regulatory pressures, reducing carbon emissions in maritime transport has become a priority. Shipping companies face the challenge of balancing profitability objectives with the imperative to minimize their environmental footprint. This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. The Gale–Shapley algorithm is employed to achieve stable vessel–cargo matching, and the genetic algorithm is adopted for iterative optimization. This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. The findings provide valuable theoretical guidance for shipping companies navigating increasingly stringent CII regulations.https://www.mdpi.com/2077-1312/13/4/752tramp ship routing and schedulingcarbon intensity indicatorbi-objective optimization modelGale–Shapley algorithmgenetic algorithm |
| spellingShingle | Haiying Yang Feiyang Ren Jingbo Yin Siqi Wang Rafi Ullah Khan Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization Journal of Marine Science and Engineering tramp ship routing and scheduling carbon intensity indicator bi-objective optimization model Gale–Shapley algorithm genetic algorithm |
| title | Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization |
| title_full | Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization |
| title_fullStr | Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization |
| title_full_unstemmed | Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization |
| title_short | Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization |
| title_sort | tramp ship routing and scheduling with integrated carbon intensity indicator cii optimization |
| topic | tramp ship routing and scheduling carbon intensity indicator bi-objective optimization model Gale–Shapley algorithm genetic algorithm |
| url | https://www.mdpi.com/2077-1312/13/4/752 |
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