Article(id=1240655138944250130, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.03.015, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720627200000, receivedDateStr=2024-07-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773724835382, onlineDateStr=2026-03-17, pubDate=1758729600000, pubDateStr=2025-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773724835382, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773724835382, creator=13701087609, updateTime=1773724835382, updator=13701087609, issue=Issue{id=1240655131507740845, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='3', pageStart='1', pageEnd='184', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773724833608, creator=13701087609, updateTime=1773725188865, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656621609742880, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656621613937185, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=121, endPage=128, ext={EN=ArticleExt(id=1240655140533891359, articleId=1240655138944250130, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Collaborative optimization of fuel bunkering and voyage speed for routes of alternative fuel bulk carrier, columnId=1240655020656489358, journalTitle=Navigation of China, columnName=Green Shipping, runingTitle=null, highlight=null, articleAbstract=

In response to increasingly stringent maritime emission regulations, vessels using alternative fuels—such as Liquefied Natural Gas (LNG) and methanol—are being gradually deployed. However, the number of ports offering bunkering for these new fuels remains significantly lower than those supplying conventional fuels, making route planning and operational management more challenging for alternatively fueled vessels. Shipping companies urgently need to rationally design routes and support the operation of alternative fuel bulk carriers within the context of scarce refueling infrastructure. To this end, this study develops a mixed-integer nonlinear programming (MINLP) model aiming to minimize total emissions, incorporating constraints such as total voyage duration and adjustable speed ranges. To address the nonlinear nature of the model, a heuristic algorithm based on variable neighborhood search is proposed to efficiently obtain near-optimal solutions. Finally, through case studies under both single-voyage and continuous-voyage scenarios, the collaborative optimization of refueling strategies and speed adjustments is thoroughly analyzed, demonstrating the effectiveness of the proposed model and algorithm.

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为响应日趋严苛的航运排放法规,采用液化天然气(LNG)和甲醇等新能源的船舶正逐步投入使用。但是能够提供新燃料加注服务的港口数量远少于传统燃油补给点,这使得新燃料船的航线运营规划更加困难。航运公司急需在加注站点稀缺的环境中,合理规划航线、助力新燃料散货船营运。为此本研究以总排放量最小化为目标,在考虑航程总时间和船舶速度可调范围等约束条件的基础上,构建了一种混合整数非线性规划数学模型。针对模型非线性特性,提出了一种变邻域框架的启发式求解算法,以高效获取近似最优解。最后,通过单航次及连续航次两种典型航线场景的案例研究,深入解析了燃料补给策略与航速的协同优化决策,验证了所提模型与算法的有效性。

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黄珍平(1989—),男,副研究员,研究方向为船舶能效和智能船舶。E-mail:

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黄珍平(1989—),男,副研究员,研究方向为船舶能效和智能船舶。E-mail:

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黄珍平(1989—),男,副研究员,研究方向为船舶能效和智能船舶。E-mail:

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新燃料散货船航线的燃料加注和航速协同优化
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黄珍平 1 , 赵科 2 , 季盛 1
中国航海 | 绿色航运 2025,48(3): 121-128
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中国航海 | 绿色航运 2025, 48(3): 121-128
新燃料散货船航线的燃料加注和航速协同优化
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黄珍平1 , 赵科2, 季盛1
作者信息
  • 1.上海船舶运输科学研究所有限公司 水路交通控制全国重点实验室,上海 200135
  • 2.中国远洋海运集团有限公司,上海 200135
  • 黄珍平(1989—),男,副研究员,研究方向为船舶能效和智能船舶。E-mail:

Collaborative optimization of fuel bunkering and voyage speed for routes of alternative fuel bulk carrier
Zhenping HUANG1 , Ke ZHAO2, Sheng JI1
Affiliations
  • 1.State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co., Ltd., Shanghai 200135, China
  • 2.COSCO Shipping Co., Ltd., Shanghai 200135, China
出版时间: 2025-09-25 doi: 10.3969/j.issn.1000-4653.2025.03.015
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为响应日趋严苛的航运排放法规,采用液化天然气(LNG)和甲醇等新能源的船舶正逐步投入使用。但是能够提供新燃料加注服务的港口数量远少于传统燃油补给点,这使得新燃料船的航线运营规划更加困难。航运公司急需在加注站点稀缺的环境中,合理规划航线、助力新燃料散货船营运。为此本研究以总排放量最小化为目标,在考虑航程总时间和船舶速度可调范围等约束条件的基础上,构建了一种混合整数非线性规划数学模型。针对模型非线性特性,提出了一种变邻域框架的启发式求解算法,以高效获取近似最优解。最后,通过单航次及连续航次两种典型航线场景的案例研究,深入解析了燃料补给策略与航速的协同优化决策,验证了所提模型与算法的有效性。

新燃料船  /  协同优化  /  燃料加注策略  /  航速优化

In response to increasingly stringent maritime emission regulations, vessels using alternative fuels—such as Liquefied Natural Gas (LNG) and methanol—are being gradually deployed. However, the number of ports offering bunkering for these new fuels remains significantly lower than those supplying conventional fuels, making route planning and operational management more challenging for alternatively fueled vessels. Shipping companies urgently need to rationally design routes and support the operation of alternative fuel bulk carriers within the context of scarce refueling infrastructure. To this end, this study develops a mixed-integer nonlinear programming (MINLP) model aiming to minimize total emissions, incorporating constraints such as total voyage duration and adjustable speed ranges. To address the nonlinear nature of the model, a heuristic algorithm based on variable neighborhood search is proposed to efficiently obtain near-optimal solutions. Finally, through case studies under both single-voyage and continuous-voyage scenarios, the collaborative optimization of refueling strategies and speed adjustments is thoroughly analyzed, demonstrating the effectiveness of the proposed model and algorithm.

alternative fuel vessel  /  collaborative optimization  /  fuel bunkering strategy  /  speed optimization
黄珍平, 赵科, 季盛. 新燃料散货船航线的燃料加注和航速协同优化. 中国航海, 2025 , 48 (3) : 121 -128 . DOI: 10.3969/j.issn.1000-4653.2025.03.015
Zhenping HUANG, Ke ZHAO, Sheng JI. Collaborative optimization of fuel bunkering and voyage speed for routes of alternative fuel bulk carrier[J]. Navigation of China, 2025 , 48 (3) : 121 -128 . DOI: 10.3969/j.issn.1000-4653.2025.03.015
2025年第48卷第3期
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doi: 10.3969/j.issn.1000-4653.2025.03.015
  • 接收时间:2024-07-11
  • 首发时间:2026-03-17
  • 出版时间:2025-09-25
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  • 收稿日期:2024-07-11
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    1.上海船舶运输科学研究所有限公司 水路交通控制全国重点实验室,上海 200135
    2.中国远洋海运集团有限公司,上海 200135
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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