Locating and deploying essential goods and equipment in disasters using AI-enabled approaches: A systematic literature review

被引：3

作者：

Farazmehr, Shima ^{[1
]}

Wu, Yong ^{[2
]}

机构：

[1] Australian Natl Univ, Coll Business & Econ, Res Sch Management, Canberra, ACT 2600, Australia

[2] Griffith Univ, Dept Business Strategy & Innovat, Gold Coast Campus, Southport, Qld 4222, Australia

来源：

PROGRESS IN DISASTER SCIENCE | 2023年 / 19卷

关键词：

Disaster management; Resilience; Artificial intelligence; Essential goods locating and deployment; VEHICLE-ROUTING PROBLEM; SIMULATED ANNEALING ALGORITHM; PARTICLE SWARM OPTIMIZATION; NEURAL-NETWORKS; SOCIAL MEDIA; BIG DATA; HUMANITARIAN LOGISTICS; FACILITY LOCATION; RELIEF LOGISTICS; MANAGEMENT;

D O I：

10.1016/j.pdisas.2023.100292

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Locating, routing and deploying essential goods and equipment are proactive disaster management strategies which received attention during recent decades. Many artificial intelligence (AI) based methods have been applied to respond to disasters in the past decade. However, there lacks a systematic review on these approaches. This paper reviews such papers published over the period of 2012-2022. These publications were examined according to their goal of using AI-based methods (e.g., for disaster management or for essential goods and equipment locating and deployment). We examined the approaches adopted and their specific application areas within the broad spectrum of disaster management. Based on our review, we recommend a few areas which could benefit from AI-based methods, especially for the less explored area of locating and routing problem during disasters. This research would be helpful for academics and practitioners alike in effectively adopting AI methods to improve the resilience and response in disastrous events.

引用

页数：12