Emergency facility location problems in logistics: Status and perspectives

被引:57
|
作者
Wang, Wei [1 ,2 ]
Wu, Shining [2 ]
Wang, Shuaian [1 ,2 ]
Zhen, Lu [3 ]
Qu, Xiaobo [4 ]
机构
[1] Hong Kong Polytech Univ, Shenzhen Res Inst, Shenzhen 518057, Peoples R China
[2] Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
[3] Shanghai Univ, Sch Management, Shang Da Rd 99, Shanghai 200444, Peoples R China
[4] Chalmers Univ Technol, Dept Architecture & Civil Engn, S-41296 Gothenburg, Sweden
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Emergency facility location; Emergency service; Covering problem; Mathematical modeling; STOCHASTIC-PROGRAMMING APPROACH; SET-COVERING PROBLEM; MEDICAL-SERVICE; AMBULANCE LOCATION; DYNAMIC REDEPLOYMENT; FIRE COMPANIES; SIZING PROBLEM; FLEET MODEL; OPTIMIZATION; COVERAGE;
D O I
10.1016/j.tre.2021.102465
中图分类号
F [经济];
学科分类号
02 ;
摘要
Emergencies that pose potential threats to our health, life, and properties can happen anywhere and anytime and may result in huge losses if they are not handled timely and effectively. An immediate response to emergencies is the key to mitigate these threats and losses. As the response time is largely dependent on the number and location of emergency facilities, the problem of how to determine the optimal number of emergency facilities and their best locations is of great strategic importance and of great interest to researchers. One of the most common approaches for researchers to address the emergency facility location problem is to model it as a discrete coverage-based emergency facility location problem. This paper provides a comprehensive overview of this problem, including mathematical models and their extensions and applications. In addition, the commonly used solution methods and some promising future research questions based on covering models are discussed.
引用
收藏
页数:24
相关论文
共 50 条
  • [1] Facility Location Problems in City Crowd Logistics
    Herrmann, E.
    Kunze, O.
    URBAN MOBILITY - SHAPING THE FUTURE TOGETHER, 2019, 41 : 117 - 134
  • [2] Facility location optimization model for emergency humanitarian logistics
    Boonmee, Chawis
    Arimura, Mikiharu
    Asada, Takumi
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2017, 24 : 485 - 498
  • [3] GIS and Optimisation: Potential Benefits for Emergency Facility Location in Humanitarian Logistics
    Rodriguez-Espindola, Oscar
    Albores, Pavel
    Brewster, Christopher
    GEOSCIENCES, 2016, 6 (02)
  • [4] Proximity, land, labor and planning? Logistics industry perspectives on facility location
    Jakubicek, Paul
    Woudsma, Clarence
    TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH, 2011, 3 (03): : 161 - 173
  • [5] Logistics of facility location and allocation.
    Zilinskas, A
    INTERFACES, 2003, 33 (01) : 99 - 100
  • [6] Robust facility location in reverse logistics
    Egri, Peter
    David, Balazs
    Kis, Tamas
    Kresz, Miklos
    ANNALS OF OPERATIONS RESEARCH, 2023, 324 (1-2) : 163 - 188
  • [7] Robust facility location in reverse logistics
    Péter Egri
    Balázs Dávid
    Tamás Kis
    Miklós Krész
    Annals of Operations Research, 2023, 324 : 163 - 188
  • [8] Distributionally robust location-allocation with demand and facility disruption uncertainties in emergency logistics
    Wang, Dujuan
    Peng, Jian
    Yang, Hengfei
    Cheng, T. C. E.
    Yang, Yuze
    COMPUTERS & INDUSTRIAL ENGINEERING, 2023, 184
  • [10] Proposal of a Logistics Solution for an Emergency at a Nuclear Facility
    Vegsoova, Olga
    Straka, Martin
    Kysel'a, Kamil
    ROCZNIK OCHRONA SRODOWISKA, 2020, 22 (01): : 156 - 170