• DocumentCode
    3520177
  • Title

    Optimal Supply Location Selection and Routing for Emergency Material Delivery

  • Author

    Han, Yunjun ; Guan, Xiaohong ; Shi, Leyuan

  • Author_Institution
    Tsinghua Univ., Beijing
  • fYear
    2007
  • fDate
    22-25 Sept. 2007
  • Firstpage
    1039
  • Lastpage
    1044
  • Abstract
    Supplying emergent materials for a disaster area in time plays a vital role in emergency response. Supply location selection and routing problem including warehouse selection and fleets scheduling and routing to guarantee to meet the demand in the required time window considered in this paper is a new and difficult problem and is proved to be NP-hard. The salient feature of this problem lies in the incorporation of the location selection into the problem. Moreover, every supply source can send a commodity to any customer such that the supply system makes full use of the commodities among different warehouses. The jam caused by heavy traffic is also considered in our problem. Clearly this problem is closer to the requirements in a practical emergency response system and is solved with ILOG CPLEX for a small and medium scale problem. The numerical testing results show that our problem formulation is valid and is difficult to solve. It is also shown that the total transportation cost increases as the demand deadlines become tighter and the number of commodities is larger. The computational times generally become intolerable for problems with more than 60 nodes.
  • Keywords
    computational complexity; optimisation; transportation; ILOG CPLEX; NP-hard problem; disaster area; emergency material delivery routing; fleets scheduling; optimal supply location selection; practical emergency response system; routing problem; warehouse selection; Automation; Costs; Disaster management; Heuristic algorithms; Job shop scheduling; Routing; Testing; Transportation; USA Councils; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering, 2007. CASE 2007. IEEE International Conference on
  • Conference_Location
    Scottsdale, AZ
  • Print_ISBN
    978-1-4244-1154-2
  • Electronic_ISBN
    978-1-4244-1154-2
  • Type

    conf

  • DOI
    10.1109/COASE.2007.4341789
  • Filename
    4341789