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[1]王金强,于竞宇,张琼,等.基于概率最大覆盖的水上险情应急设施选址研究*[J].中国安全生产科学技术,2025,21(4):182-188.[doi:10.11731/j.issn.1673-193x.2025.04.024]
　WANG Jinqiang,YU Jingyu,ZHANG Qiong,et al.Research on site selection of waterborne hazard emergency facilities based on maximum probability coverage[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2025,21(4):182-188.[doi:10.11731/j.issn.1673-193x.2025.04.024]
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基于概率最大覆盖的水上险情应急设施选址研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
21
期数:
2025年4期
页码:
182-188
栏目:
职业安全卫生管理与技术
出版日期:
2025-04-30

文章信息/Info

Title:
Research on site selection of waterborne hazard emergency facilities based on maximum probability coverage
文章编号:
1673-193X(2025)-04-0182-07
作者:
王金强; 于竞宇; 张琼; 吴继成; 王静峰; 林威
(1.合肥工业大学 土木与水利工程学院，安徽 合肥 230009；
2.安徽建工交通航务集团有限公司，安徽 合肥 230000；
3.安徽省招标集团股份有限公司，安徽 合肥 230051)
Author(s):
WANG Jinqiang;  YU Jingyu;  ZHANG Qiong;  WU Jicheng;  WANG Jingfeng;  LIN Wei
(1.School of Civil and Hydraulic Engineering,Hefei University of Technology,Hefei Anhui 230009,China;
2.AnHui Traffic & Shipping Engineering Co.,Ltd.,Hefei Anhui 230000,China;
3.Anhui Tendering Group Co.,Ltd.,Hefei Anhui 230051,China)
关键词:
水上险情; 应急设施选址; 概率最大覆盖; 人工蜂群算法
Keywords:
waterborne hazard;  site selection of emergency facility;  maximum probability coverage;  artificial bee colony algorithm
分类号:
X913
DOI:
10.11731/j.issn.1673-193x.2025.04.024
文献标志码:
A
摘要:
为优化水上险情应急设施选址，基于概率最大覆盖模型构建考虑水上险情救援拥挤情况的应急设施选址模型，提出1种利用共轭梯度法对人工蜂群算法进行局部改进的算法。对该模型进行求解，并将求解结果与ALNS算法在公开数据集上进行算例对比验证。研究结果表明：改进人工蜂群算法的计算结果基本接近基准值，且其收敛速度明显快于ALNS算法的标准收敛时间，证明了改进人工蜂群算法的科学性和有效性。同时在考虑到拥挤情况下，处理概率最大覆盖模型时改进人工蜂群算法的收敛速度要显著优于ALNS算法。研究结果可为水上应急救援网络规划、拥堵环境下多目标设施选址优化提供参考。
Abstract:
In order to optimize the site selection of emergency facilities for waterborne hazard,a model for the site selection of emergency facilities considering the rescue congestion of waterborne hazard was constructed based on the maximum probability coverage model,and an algorithm for local improvement of artificial bee colony algorithm using conjugate gradient method was proposed.The model was solved,and the solution results were verified by comparing with the ALNS algorithm on public datasets in terms of arithmetic cases.The results show that the computational results of the improved artificial bee colony algorithm are basically close to the benchmark value,and its convergence speed is significantly faster than the standard convergence time of the ALNS algorithm,which proves the scientific validity and effectiveness of the improved artificial bee colony algorithm.Meanwhile,the convergence speed of the improved artificial bee colony algorithm is significantly better than that of the ALNS algorithm when dealing with the maximum probability coverage model considering the congestion situation.The research results can provide reference for the waterborne emergency rescue network planning and multi-objective facility siting optimization under congested environment.

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备注/Memo

备注/Memo:
收稿日期： 2024-09-19
* 基金项目： 安徽省交通运输重点科技项目（2021-KJQD-019）
作者简介： 王金强，硕士研究生，主要研究方向为工程管理。
通信作者： 林威，硕士，主要研究方向为工程管理。
更新日期/Last Update: 2025-04-28