Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty

PLoS One. 2015 Sep 29;10(9):e0139132. doi: 10.1371/journal.pone.0139132. eCollection 2015.

Abstract

Natural disasters occur frequently in recent years, causing huge casualties and property losses. Nowadays, people pay more and more attention to the emergency logistics problems. This paper studies the emergency logistics problem with multi-center, multi-commodity, and single-affected-point. Considering that the path near the disaster point may be damaged, the information of the state of the paths is not complete, and the travel time is uncertainty, we establish the nonlinear programming model that objective function is the maximization of time-satisfaction degree. To overcome these drawbacks: the incomplete information and uncertain time, this paper firstly evaluates the multiple roads of transportation network based on grey theory and selects the reliable and optimal path. Then simplify the original model under the scenario that the vehicle only follows the optimal path from the emergency logistics center to the affected point, and use Lingo software to solve it. The numerical experiments are presented to show the feasibility and effectiveness of the proposed method.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Civil Defense / methods*
  • Computer Simulation
  • Disasters*
  • Humans
  • Models, Theoretical*
  • Transportation

Grants and funding

This paper was partially supported by the National Natural Science Foundation of China (NSFC) (Grant Nos. 71201093, 71571111), Independent Innovation Foundation of Shandong University, IIFSDU (Grant No. IFYT14011), and the Foundation of University of Jinan (Grant No XKY1414).