Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm
Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To add...
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MDPI AG
2025-04-01
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| author | Zhao Li Hao Zhang Jinfeng Zhang Bo Wu |
| author_facet | Zhao Li Hao Zhang Jinfeng Zhang Bo Wu |
| author_sort | Zhao Li |
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| description | Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. The case study results demonstrate that the proposed approach can reduce operating costs by more than 15% compared to conventional route and speed strategies while also effectively decreasing emissions of CO<sub>2</sub>, NOx, SOx, PM, and CO. Additionally, comparative experiments reveal that the designed algorithm outperforms both the GA and the Linear Interactive and General Optimizer (LINGO) solver for identifying optimal route and speed solutions. This research provides critical insights into the operational dynamics of methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies for conventional fuel vessels are not directly applicable. This study provides critical insights into the optimization of voyage decision-making for methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies designed for conventional fuel vessels are not directly applicable. It further elucidates the impact of methanol fuel tank capacity on voyage planning, revealing that larger tank capacities offer greater operational flexibility and improved economic performance. These findings provide valuable guidance for shipping companies in strategically planning methanol dual-fuel operations, enhancing economic efficiency while reducing vessel emissions. |
| format | Article |
| id | doaj-art-6f66ce779dd74a8085f4eac79c1c8fbe |
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| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Big Data and Cognitive Computing |
| spelling | doaj-art-6f66ce779dd74a8085f4eac79c1c8fbe2025-08-20T02:28:19ZengMDPI AGBig Data and Cognitive Computing2504-22892025-04-01949010.3390/bdcc9040090Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic AlgorithmZhao Li0Hao Zhang1Jinfeng Zhang2Bo Wu3School of Navigation, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Management, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Navigation, Wuhan University of Technology, Wuhan 430000, ChinaSchool of Navigation, Wuhan University of Technology, Wuhan 430000, ChinaEffective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. The case study results demonstrate that the proposed approach can reduce operating costs by more than 15% compared to conventional route and speed strategies while also effectively decreasing emissions of CO<sub>2</sub>, NOx, SOx, PM, and CO. Additionally, comparative experiments reveal that the designed algorithm outperforms both the GA and the Linear Interactive and General Optimizer (LINGO) solver for identifying optimal route and speed solutions. This research provides critical insights into the operational dynamics of methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies for conventional fuel vessels are not directly applicable. This study provides critical insights into the optimization of voyage decision-making for methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies designed for conventional fuel vessels are not directly applicable. It further elucidates the impact of methanol fuel tank capacity on voyage planning, revealing that larger tank capacities offer greater operational flexibility and improved economic performance. These findings provide valuable guidance for shipping companies in strategically planning methanol dual-fuel operations, enhancing economic efficiency while reducing vessel emissions.https://www.mdpi.com/2504-2289/9/4/90methanol dual-fuel-powered shipsroute and speed optimizationMINLP modelGALINGO solver |
| spellingShingle | Zhao Li Hao Zhang Jinfeng Zhang Bo Wu Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm Big Data and Cognitive Computing methanol dual-fuel-powered ships route and speed optimization MINLP model GA LINGO solver |
| title | Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm |
| title_full | Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm |
| title_fullStr | Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm |
| title_full_unstemmed | Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm |
| title_short | Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm |
| title_sort | joint optimization of route and speed for methanol dual fuel powered ships based on improved genetic algorithm |
| topic | methanol dual-fuel-powered ships route and speed optimization MINLP model GA LINGO solver |
| url | https://www.mdpi.com/2504-2289/9/4/90 |
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