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基于物资分类的人道物流中的救灾需求计算。

Relief Demand Calculation in Humanitarian Logistics Using Material Classification.

机构信息

School of Management, Hefei University of Technology, Hefei 230000, China.

School of Management, University of Science and Technology of China, Hefei 230000, China.

出版信息

Int J Environ Res Public Health. 2020 Jan 16;17(2):582. doi: 10.3390/ijerph17020582.

DOI:10.3390/ijerph17020582
PMID:31963215
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7013424/
Abstract

Demand calculation, which is the base of most logistics decisions and activities, is a critical work in humanitarian logistics (HL). However, previous studies on demand calculation in HL mainly focus on demand forecasting methodology, with many neglecting the checklist of critical supplies and practice background. This work proposes a new method for relief demand calculation by dividing the process into two parts: supply classification and demand calculation. A general method for classifying relief supplies and clarifying the checklist of relief items for multi-disaster and multiple natural scenarios is given in detail, followed by the procedure of demand calculation for each relief material. The authors present a case study to validate the feasibility and effectiveness of the proposed method based on the disaster response practice in China. Detailed lists of relief demand for different types and severities of disaster are provided.

摘要

需求计算是大多数物流决策和活动的基础,也是人道主义物流(HL)中的一项关键工作。然而,之前关于 HL 中的需求计算的研究主要集中在需求预测方法上,许多研究忽略了关键物资清单和实践背景。本工作通过将过程分为两部分,提出了一种新的救灾需求计算方法:供应分类和需求计算。详细给出了一种分类救灾物资和明确多灾种、多自然情景下救灾物资清单的通用方法,然后给出了每种救灾物资的需求计算程序。作者根据中国的灾害应对实践,提出了一个案例研究来验证该方法的可行性和有效性。给出了不同类型和严重程度灾害的详细救灾需求清单。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/91c6882b86a5/ijerph-17-00582-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/123c12e9c10c/ijerph-17-00582-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/f03024e99ef1/ijerph-17-00582-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/0b82b9cdf624/ijerph-17-00582-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/0e10a4af09b0/ijerph-17-00582-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/91c6882b86a5/ijerph-17-00582-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/123c12e9c10c/ijerph-17-00582-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/f03024e99ef1/ijerph-17-00582-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/0b82b9cdf624/ijerph-17-00582-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/0e10a4af09b0/ijerph-17-00582-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9e7/7013424/91c6882b86a5/ijerph-17-00582-g005.jpg

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