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中国管理科学 ›› 2017, Vol. 25 ›› Issue (6): 143-150.doi: 10.16381/j.cnki.issn1003-207x.2017.06.015

• 论文 • 上一篇    下一篇

多类应急资源配置的鲁棒选址-路径优化

彭春, 李金林, 王珊珊, 冉伦   

  1. 北京理工大学管理与经济学院, 北京 100081
  • 收稿日期:2016-05-04 修回日期:2016-07-29 出版日期:2017-06-20 发布日期:2017-08-26
  • 通讯作者: 李金林(1955-),男(汉族),北京理工大学管理与经济学院,教授,博士生导师,研究方向:医疗与健康数据分析与决策、收益管理,E-mail:jinlinli@bit.edu.cn. E-mail:jinlinli@bit.edu.cn.
  • 基金资助:

    国家自然科学基金资助重点项目(71432002);国家自然科学基金面上资助项目(71172172);北京理工大学研究生国际学术交流项目(1320012351601)

Multiple Relief Resources Robust Location-Routing Optimization

PENG Chun, LI Jin-lin, WANG Shan-shan, RAN Lun   

  1. School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China
  • Received:2016-05-04 Revised:2016-07-29 Online:2017-06-20 Published:2017-08-26

摘要: 本文基于应急资源配置的灾前预防准备和灾后的响应分配,在多类应急资源配置选址-路径优化名义模型的基础上,考虑多类应急资源成本的不确定性,引入两类不确定集合(box和ellipsoid)刻画该不确定性,分别建立多类应急资源鲁棒选址-路径优化模型,运用鲁棒优化方法,将其转化为易求解处理的鲁棒等价模型,并通过CPLEX和GAMS混合编程算法求解。最后,本文对我国四川北部和西部自然灾害多发区的19个县市进行应急资源优化配置分析,确定应急资源临时供应点的最优选址布局、应急资源的分配路径,同时考虑扰动比例的灵敏度分析,验证模型的可行性和有效性。结果表明在其他条件相同的情况下,ellipsoid不确定集合下的鲁棒模型较保守,配置的总成本较高,因此决策者可以根据自己的风险厌恶程度选择不确定水平参数的值,确定应急资源的配置方案,进而为相关应急救灾部门在灾前预防准备工作提供决策支持。

关键词: 应急资源, 选址-路径, 成本不确定性, 鲁棒优化, 不确定集合

Abstract: Decisions to support preparedness activities for disastermanagement are challenging due to the uncertainties of parameters, the balance preparedness and risk, so it is a hot topic. In this paper multiple relief resources location-routing problem is addressed to determine optimal deployment of supply facilities for multiple relief resources, transport distribution route. However, traditional methods addressing this problem mainly focus on stochastic optimization by assuming probability distribution to measure the uncertainty, there are some drawbacks. Multiple relief resources cost uncertainty is considered, introducing two types of uncertainty sets, i.e. box and ellipsoid, to capture the uncertain cost of multiple relief resources, and multiple relief resources robust location-routing models are proposed respectively, which are converted into the deterministic robust equivalent models, and can be solved by hybrid programming algorithm coded in GAMS and CPLEX. Finally, the 19 cities in the north and west of Sichuan Province are chosen to conduct the numerical study. Results show that the proposed robust models is feasible and effective, and compared to the robust model based on box uncertainty set, under the same parameter setting, robust model based on ellipsoid uncertainty set usually is more conservative, and leads to a higher total cost. Decision-makers, according to their risk aversion and conservativeness, choose an appropriate value for the uncertain level parameters Γ/Ω to get the optimal solution, and provide decision support to the department of Emergency Disaster Relief.

Key words: relief resource, location-routing, cost uncertainty, robust optimization, uncertainty set

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