Title: Optimal matching of urban emergency resources under major public health events by multi-expert decision model of grey situations

Authors: Haitao Li

Addresses: School of Civil Engineering and Architecture, Anyang Normal University, No. 436 Xiange Road, Wenfeng District, 455000, Anyang, China

Abstract: It is a difficult issue to have optimal matching emergency resources among multiple epidemic areas and multiple emergency resources when information is poor, especially in the early stage of a major public health event. This article tries to make full use of the experiences and wisdom of experts from various fields, to build a multi-expert decision model combined with the multi-objective grey situation method, and hopes to improve the efficiency and the quality of emergency resources allocation. Firstly taking the COVID-19 epidemic as an example to describe the modelling framework; then processing the three common types of uncertain decision information into the type of normalised utility value, putting forward a linear combination algorithm to determine aggregating weights of group decision information; finally giving the implementation steps of the proposed method and presents an application case to illustrate its practical feasibility and effectiveness. This article also contributes to the other public emergencies decision-making.

Keywords: major public health events; emergency resources matching; grey situation group decision; multiple uncertain preferences; COVID-19 epidemic.

DOI: 10.1504/IJADS.2022.125481

International Journal of Applied Decision Sciences, 2022 Vol.15 No.5, pp.559 - 577

Received: 21 Dec 2020
Accepted: 31 May 2021
Published online: 12 Sep 2022 *

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