中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (9): 173-180.doi: 10.16265/j.cnki.issn1003-3033.2019.09.028

• 公共安全 • 上一篇    下一篇

风险不确定的海上应急物资储备库选址

张聆晔, 吕靖 教授   

  1. 大连海事大学 交通运输工程学院,辽宁 大连 116026
  • 收稿日期:2019-05-15 修回日期:2019-07-21 出版日期:2019-09-28 发布日期:2020-10-30
  • 作者简介:张聆晔 (1994—),男,四川成都人,博士研究生,主要研究方向为交通运输规划与管理。E-mail:talentzly@hotmail.com。
  • 基金资助:
    国家自然科学基金资助(71473023);中央高校基本科研业务费专项资金资助(3132016359);国家社科基金重大专项资助(18VHQ005)。

Location of maritime emergency supplies repertories considering risk uncertainty

ZHANG Lingye, LYU Jing   

  1. College of Transportation Engineering, Dalian Maritime University, Dalian Liaoning 116026, China
  • Received:2019-05-15 Revised:2019-07-21 Online:2019-09-28 Published:2020-10-30

摘要: 为提升海上应急系统的救助服务能力,研究海上应急物资储备库的选址问题。首先根据海上应急特点,从及时性、有效性以及不同风险等级的事故对应急服务需求量的差异性等角度考虑,引入应急效率满意度的概念,并将最大化应急效率值作为目标,构建海上应急物资储备库选址模型;然后通过离散仿真情景分析海上事故风险整体分布的不确定性,并利用鲁棒理论构建关于储备库选址的鲁棒优化模型;最后采用遗传算法求得最终选址方案。结果表明:在风险分布具有显著差异的离散仿真情景中,鲁棒优化模型相比确定性模型而言具有较好的稳定性,能够确保选址方案的可靠性。

关键词: 应急物资储备库, 风险等级, 选址模型, 鲁棒优化, 遗传算法

Abstract: In order to improve the rescue service capability of maritime emergency system, site selection of maritime emergency material reserve was studied. Firstly, according to the characteristics of maritime emergency response, the concept of emergency response satisfaction was introduced from the perspectives of timeliness, effectiveness and the difference in the demand for emergency response services among accidents with different risk levels. Based on this, a site selection model of marine emergency material reserve was constructed to realize the maximization of emergency efficiency. Then the uncertainty of the overall distribution of risk value of maritime accidents was analyzed by discrete simulation scenarios, and the robust optimization model of the location of storage pool was constructed by using robust theory. Finally, genetic algorithm was used to obtain the final location scheme. The results show that in discrete simulation scenarios with significant difference in risk distribution, the proposed robust optimization model are more stable than deterministic model and it can ensure the reliability of the location scheme.

Key words: emergency supplies repertories, risk level, location model, robust optimization, genetic algorithm

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