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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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, authorsList=薛清仁, 程亮, 吴洁, 宋彦杰)}, authors=[Author(id=1240655519367622708, tenantId=1146029695717560320, journalId=1240618002186551303, articleId=1240655517400494088, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=xueqingren_11@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1240655519434731577, tenantId=1146029695717560320, journalId=1240618002186551303, articleId=1240655517400494088, authorId=1240655519367622708, language=EN, stringName=Qingren XUE, firstName=Qingren, middleName=null, lastName=XUE, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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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: xueqingren_11@163.com
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