Article(id=1240655023697351607, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655017040991028, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.04.016, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1727280000000, receivedDateStr=2024-09-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773724807905, onlineDateStr=2026-03-17, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773724807905, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773724807905, creator=13701087609, updateTime=1773724807905, updator=13701087609, issue=Issue{id=1240655017040991028, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='4', pageStart='1', pageEnd='199', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773724806318, creator=13701087609, updateTime=1773725219619, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656750618145316, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655017040991028, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656750618145317, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655017040991028, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=141, endPage=151, ext={EN=ArticleExt(id=1240655025102443513, articleId=1240655023697351607, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Research on Arctic route planning based on multi-objective optimization model, columnId=1240655021340160960, journalTitle=Navigation of China, columnName=Intelligent Shipping, runingTitle=null, highlight=null, articleAbstract=

To address the safety and economic requirements for ships navigating the complex ice environments of Arctic waters, this paper proposes a multi-objective improved Sparrow Search Algorithm (SSA) to optimize both wind resistance and ice resistance. The Risk Index Outcome (RIO), calculated by the Polar Operational Limit Assessment Risk Indexing System (POLARIS), and the safe water depth threshold are adopted as constraints to ensure navigation safety and mitigate the impact of resistance on navigation efficiency along Arctic routes. First, meteorological and ice data for the Arctic route are processed, and a grid environment map is constructed according to ship type. Second, safe navigable areas are identified, and a multi-objective function model is established. Finally, the improved sparrow search algorithm is applied to optimize the route and is compared with other typical path planning algorithms to verify the effectiveness and feasibility of the proposed method. The results indicate that the optimal path generated by the improved sparrow search algorithm, based on the multi-objective model of wind and ice resistance, can significantly reduce ship resistance during navigation-achieving a reduction of up to 10.9%. Moreover, there is no significant difference in path length or running time compared with other algorithms. This study provides an economical and reliable optimization solution for ship navigation in Arctic routes.

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基于北极海域复杂海冰环境给船舶航行安全与经济效益带来的诸多挑战，文章提出一种优化航行风速阻力和冰阻力的多目标改进麻雀搜索路径规划算法。以极地操作限制风险评估系统计算所得的风险指数和安全水深阈值作为约束条件来确保船舶的航行安全，减少了北极航道中外界阻力对船舶航行的影响。首先，对北极航道的气象要素和海冰数据进行处理，结合船舶类型构建栅格环境地图；其次，筛选可安全通航区域，建立多目标函数模型；最后，利用改进的麻雀搜索算法对航线进行优化，并与其他典型路径规划算法对比分析，以此验证该方法的有效性与可行性。结果表明，基于风阻和冰阻力多目标模型的改良麻雀搜索算法所生成的最优路径能够显著减少船舶航行中所受阻力，最优可缩小10.9%，且路径长短和运行时间与其他算法相比无明显差异，为北极航道中船舶的航行提供了经济、高效的优化方案。

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