• DocumentCode
    2110872
  • Title

    Ant Colony Optimization for Facility Location for Large-Scale Emergencies

  • Author

    Lu, Xiang-lin ; Hou, Yun-Xian

  • Author_Institution
    Coll. of Econ. & Manage., CAU, Beijing, China
  • fYear
    2009
  • fDate
    20-22 Sept. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The sitting of emergency service facilities plays a crucial role in determining the efficiency of safety protection and emergency response. Research on emergency service facilities is abundant. However, this research does not typically address the particular conditions that arise when locating facilities to service large-scale emergencies, such as earthquakes, terrorist attacks, etc. In this paper, we form an improved model for determining the facility locations in response to large-scale emergencies, based on Jia, Ordonez, and Dessouky ´s research. The problem is formulated as a maximal covering problem with multiple facility quantity-of-coverage requirements. In this paper, ant colony optimization (ACO) algorithm is developed to solve the Large-scale emergency location problem. We evaluate the performance of the model and algorithm by using illustrative emergency examples. We show that the model and ACO algorithm provides an effective method to facility location for large-Scale Emergencies.
  • Keywords
    emergency services; facility location; optimisation; ant colony optimization; emergency response; emergency service facility; facility location; large-scale emergency location problem; maximal covering problem; quantity-of-coverage requirement; safety protection; Ant colony optimization; Disaster management; Earthquakes; Educational institutions; Emergency services; Environmental economics; Large-scale systems; Protection; Safety; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science, 2009. MASS '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4638-4
  • Electronic_ISBN
    978-1-4244-4639-1
  • Type

    conf

  • DOI
    10.1109/ICMSS.2009.5302451
  • Filename
    5302451