Citation

Feng Z, Li G, Wang W, Zhang L, Xiang W, He X, Zhang M, Wei N. Int. J. Disaster Risk Reduct. 2023; 96: e103921.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2023.103921

PMID

unavailable

Abstract

Public health events and natural disaster emergencies often cause logistical disruptions and shortages of supplies for residents in the affected areas. The construction of emergency logistics centers (ELCs) can enable relief to reach the affected areas faster, so the ELCs site selection is critical. This study proposes a novel approach based on Multi-Criteria Decision-Making (MCDM) and Geographic Information System (GIS) to solve the ELCs site selection problem. Firstly, nine criteria affecting ELCs site selection are identified, the criteria spatial data are collected and the criteria normalized layers are created using GIS. Then, the weights of the criteria are determined by combining the entropy weight method with the Criteria Importance Though Intercrieria Correlation method (CRITIC), and the ELCs site selection suitability map is obtained using superposition analysis. Finally, the ranking of ELCs alternatives is obtained using the Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. A case study is conducted in Xi'an which is the largest city in Northwest China, and the results indicate that (1) the population density criterion (C9) has a weight of 0.581, which accounts for the largest proportion of weight. Alternative A9 (near the New City Plaza) ranks highest among the 13 alternatives. (2) Sensitivity analysis shows that the ranking is very sensitive to changes in the criterion weights, which verifies the rationality of the combined assignment method. (3) The comparative analysis with the TOPSIS method shows that the rankings obtained by the method proposed in this paper are stable, which verifies the feasibility of the siting model.

Language: en

Keywords

Emergency logistics centers (ELCs); Geographic information system (GIS); Multi-criteria decision-making (MCDM); Site selection