Article(id=1240655517400494088, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655508231746242, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.02.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710086400000, receivedDateStr=2024-03-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773724925613, onlineDateStr=2026-03-17, pubDate=1750780800000, pubDateStr=2025-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773724925613, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773724925613, creator=13701087609, updateTime=1773724925613, updator=13701087609, issue=Issue{id=1240655508231746242, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='2', pageStart='1', pageEnd='180', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773724923427, creator=13701087609, updateTime=1773725151164, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656463488667953, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655508231746242, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656463492862258, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655508231746242, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=16, endPage=24, ext={EN=ArticleExt(id=1240655517606014991, articleId=1240655517400494088, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Research on maritime search and rescue force scheduling based on DW-NSGA-Ⅱ algorithm, columnId=1240655017900823355, journalTitle=Navigation of China, columnName=Marine Traffic Safety, runingTitle=null, highlight=null, articleAbstract=

To solve the problems of complex decision-making and the difficulty of global optimisation involving many factors, this paper establishes a scheduling model for maritime search and rescue forces and uses a second-generation non-dominant genetic algorithm based on a reduplication strategy (DW-NSGA-Ⅱ) to solve these problems. Firstly, the probability of a successful search and survival (POSAS) is elaborated upon, taking into account the survival probability of the target and the relevant mathematical model of the time it takes the search and rescue force to arrive at the search area. A search and rescue force dispatch model is then established with the following optimisation goals: the maximum search success rate, the shortest arrival time of search and rescue materials, and the minimum search and rescue cost. Secondly, to solve the problems of crowding, distance failure, and poor global optimisation caused by multiple repeated solutions when solving the search and rescue force scheduling model using the second-generation non-dominant genetic algorithm (NSGA-Ⅱ), a second-generation non-dominant genetic algorithm based on a reduplication strategy (DW-NSGA-Ⅱ) is proposed. Finally, an accident is used as an example to demonstrate the use of DW-NSGA-Ⅱ and NSGA-Ⅱ to solve the model, with the resulting optimisation outcomes being compared. The experimental results show that the proposed method can consider marine environmental information, accident rescue requirements and search and rescue forces to formulate a reasonable and effective search and rescue force scheduling scheme. The DW-NSGA-Ⅱ algorithm's optimisation effect is better than that of the NSGA-Ⅱ algorithm under the same initial conditions, which verifies the superiority of DW-NSGA-Ⅱ in search and rescue force dispatch.

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针对海上搜救力量调度决策复杂、涉及因素多和全局优化难等问题,建立海上搜救力量调度模型,并采用一种基于去重策略的第二代非支配遗传算法(DW-NSGA-Ⅱ)进行求解。详细阐述考虑目标生存概率的搜寻成功率指标(POSAS)和搜救力量到达搜寻区域时间的相关数学模型,以最大搜寻成功率、最短搜救物资到达时间和最小搜救成本为优化目标建立搜救力量调度模型;针对第二代非支配遗传算法(NSGA-Ⅱ)在求解搜救力量调度模型过程中因重复解多导致拥挤距离失效、全局优化差等问题,提出一种基于去重策略的第二代非支配遗传算法(DW-NSGA-Ⅱ);以某事故为例,分别采用DW-NSGA-Ⅱ和NSGA-Ⅱ求解模型并比较优化结果。试验结果表明:所提出方法能充分考虑海洋环境信息、事故救援需求和搜救力量情况,制定合理有效的搜救力量调度方案,在相同的初始条件下,DW-NSGA-Ⅱ算法的优化效果优于NSGA-Ⅱ算法,验证DW-NSGA-Ⅱ在搜救力量调度中的优越性。

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程亮(1978—),男,教授,博士,研究方向为南海遥感、激光点云研究。E-mail:
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=B22mgHclMEAR/BGZVsnOuQ==, magXml=dtxnnd/VdkaKYDeHsZ2M1g==, pdfUrl=null, pdf=t7p3DR5UQq0Ionznmlun7g==, pdfFileSize=1977358, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=C3VAsUsQvlTT/BUoATJIBA==, mapNumber=null, authorCompany=null, fund=null, authors=

薛清仁(1997—),男,硕士研究生,研究方向为南海遥感。E-mail:

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薛清仁(1997—),男,硕士研究生,研究方向为南海遥感。E-mail:

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薛清仁(1997—),男,硕士研究生,研究方向为南海遥感。E-mail:

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基于DW-NSGA-Ⅱ算法的海上搜救力量调度研究
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薛清仁 1 , 程亮 1, 2, 3 , 吴洁 1 , 宋彦杰 4
中国航海 | 海上交通安全 2025,48(2): 16-24
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中国航海 | 海上交通安全 2025, 48(2): 16-24
基于DW-NSGA-Ⅱ算法的海上搜救力量调度研究
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薛清仁1 , 程亮1, 2, 3 , 吴洁1, 宋彦杰4
作者信息
  • 1.南京大学 地理与海洋科学学院,江苏 南京 210093
  • 2.江苏省地理信息技术重点实验室,江苏 南京 210093
  • 3.南京大学 中国南海研究协同创新中心,江苏 南京 210093
  • 4.大连海事大学 船舶导航系统国家工程研究中心,辽宁 大连 116026
  • 薛清仁(1997—),男,硕士研究生,研究方向为南海遥感。E-mail:

通讯作者:

程亮(1978—),男,教授,博士,研究方向为南海遥感、激光点云研究。E-mail:
Research on maritime search and rescue force scheduling based on DW-NSGA-Ⅱ algorithm
Qingren XUE1 , Liang CHENG1, 2, 3 , Jie WU1, Yanjie SONG4
Affiliations
  • 1.School of Geography and Ocean Science, Nanjing University, Nanjing 210093, China
  • 2.Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210093, China
  • 3.Collaborative lnnovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China
  • 4.National Engineering Research Center of Maritime Navigation System, Dalian Maritime University, Dalian 116026, China
出版时间: 2025-06-25 doi: 10.3969/j.issn.1000-4653.2025.02.003
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针对海上搜救力量调度决策复杂、涉及因素多和全局优化难等问题,建立海上搜救力量调度模型,并采用一种基于去重策略的第二代非支配遗传算法(DW-NSGA-Ⅱ)进行求解。详细阐述考虑目标生存概率的搜寻成功率指标(POSAS)和搜救力量到达搜寻区域时间的相关数学模型,以最大搜寻成功率、最短搜救物资到达时间和最小搜救成本为优化目标建立搜救力量调度模型;针对第二代非支配遗传算法(NSGA-Ⅱ)在求解搜救力量调度模型过程中因重复解多导致拥挤距离失效、全局优化差等问题,提出一种基于去重策略的第二代非支配遗传算法(DW-NSGA-Ⅱ);以某事故为例,分别采用DW-NSGA-Ⅱ和NSGA-Ⅱ求解模型并比较优化结果。试验结果表明:所提出方法能充分考虑海洋环境信息、事故救援需求和搜救力量情况,制定合理有效的搜救力量调度方案,在相同的初始条件下,DW-NSGA-Ⅱ算法的优化效果优于NSGA-Ⅱ算法,验证DW-NSGA-Ⅱ在搜救力量调度中的优越性。

海上搜救力量调度  /  NSGA-Ⅱ  /  搜救成功率  /  物资到达  /  搜救成本

To solve the problems of complex decision-making and the difficulty of global optimisation involving many factors, this paper establishes a scheduling model for maritime search and rescue forces and uses a second-generation non-dominant genetic algorithm based on a reduplication strategy (DW-NSGA-Ⅱ) to solve these problems. Firstly, the probability of a successful search and survival (POSAS) is elaborated upon, taking into account the survival probability of the target and the relevant mathematical model of the time it takes the search and rescue force to arrive at the search area. A search and rescue force dispatch model is then established with the following optimisation goals: the maximum search success rate, the shortest arrival time of search and rescue materials, and the minimum search and rescue cost. Secondly, to solve the problems of crowding, distance failure, and poor global optimisation caused by multiple repeated solutions when solving the search and rescue force scheduling model using the second-generation non-dominant genetic algorithm (NSGA-Ⅱ), a second-generation non-dominant genetic algorithm based on a reduplication strategy (DW-NSGA-Ⅱ) is proposed. Finally, an accident is used as an example to demonstrate the use of DW-NSGA-Ⅱ and NSGA-Ⅱ to solve the model, with the resulting optimisation outcomes being compared. The experimental results show that the proposed method can consider marine environmental information, accident rescue requirements and search and rescue forces to formulate a reasonable and effective search and rescue force scheduling scheme. The DW-NSGA-Ⅱ algorithm's optimisation effect is better than that of the NSGA-Ⅱ algorithm under the same initial conditions, which verifies the superiority of DW-NSGA-Ⅱ in search and rescue force dispatch.

maritime search and rescue force scheduling  /  NSGA-Ⅱ  /  Search and rescue success rate  /  supplies scheduling  /  search and rescue costs
薛清仁, 程亮, 吴洁, 宋彦杰. 基于DW-NSGA-Ⅱ算法的海上搜救力量调度研究. 中国航海, 2025 , 48 (2) : 16 -24 . DOI: 10.3969/j.issn.1000-4653.2025.02.003
Qingren XUE, Liang CHENG, Jie WU, Yanjie SONG. Research on maritime search and rescue force scheduling based on DW-NSGA-Ⅱ algorithm[J]. Navigation of China, 2025 , 48 (2) : 16 -24 . DOI: 10.3969/j.issn.1000-4653.2025.02.003
  • 国家重点研发计划项目(2022YFB3903603)
  • 国家自然科学基金(42001401)
2025年第48卷第2期
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doi: 10.3969/j.issn.1000-4653.2025.02.003
  • 接收时间:2024-03-11
  • 首发时间:2026-03-17
  • 出版时间:2025-06-25
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  • 收稿日期:2024-03-11
基金
国家重点研发计划项目(2022YFB3903603)
国家自然科学基金(42001401)
作者信息
    1.南京大学 地理与海洋科学学院,江苏 南京 210093
    2.江苏省地理信息技术重点实验室,江苏 南京 210093
    3.南京大学 中国南海研究协同创新中心,江苏 南京 210093
    4.大连海事大学 船舶导航系统国家工程研究中心,辽宁 大连 116026

通讯作者:

程亮(1978—),男,教授,博士,研究方向为南海遥感、激光点云研究。E-mail:
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2种不同金属材料的力学参数

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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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