Planning for Medical Emergency Transportation Vehicles during Natural Disasters

自然灾害 计算机科学 运输工程 医疗急救 自然(考古学) 环境规划 运筹学 环境科学 医学 历史 工程类 地理 气象学 考古
作者
Hesam Adrang,Ali Bozorgi-Amiri,Kaveh Khalili‐Damghani,Reza Tavakkoli‐Moghaddam
出处
期刊:DOAJ: Directory of Open Access Journals - DOAJ 被引量:3
标识
DOI:10.22094/joie.2020.688.1455
摘要

One of the main critical steps that should be taken during natural disasters is the assignment and distribution of resources among affected people. In such situations, this can save many lives. Determining the demands for critical items (i.e., the number of injured people) is very important. Accordingly, a number of casualties and injured people have to be known during a disaster. Obtaining an acceptable estimation of the number of casualties adds to the complexity of the problem. In this paper, a location-routing problem is discussed for urgent therapeutic services during disasters. The problem is formulated as a bi-objective Mixed-Integer Linear Programming (MILP) model. The objectives are to concurrently minimize the time of offering relief items to the affected people and minimize the total costs. The costs include those related to locations and transportation means (e.g., ambulances and helicopters) that are used to carry medical personnel and patients. To address the bi-objectiveness and verify the efficiency and applicability of the proposed model, the e-constraint method is employed to solve several randomly-generated problems with CLEPX solver in GAMS. The obtained results include the objective functions, the number of the required facility, and the trade-offs between objectives. Then, the parameter of demands (i.e., number of casualties), which has the most important role, is examined using a sensitivity analysis and the managerial insights are discussed.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
豆兼米完成签到,获得积分10
刚刚
打工人完成签到,获得积分10
刚刚
junjie完成签到,获得积分10
刚刚
阿巴阿巴发布了新的文献求助10
刚刚
ecnuzdd发布了新的文献求助10
刚刚
一加一发布了新的文献求助10
刚刚
科研通AI6.4应助光亮映波采纳,获得10
1秒前
清秀的易文完成签到,获得积分10
1秒前
1秒前
2秒前
完美世界应助www采纳,获得10
2秒前
嘻嘻完成签到 ,获得积分10
3秒前
积极向上完成签到,获得积分10
3秒前
哈哈哈哈哈完成签到,获得积分10
3秒前
牛忆丹完成签到,获得积分10
3秒前
4秒前
4秒前
4秒前
阿巴阿巴发布了新的文献求助10
4秒前
镓氧锌钇铀完成签到,获得积分0
4秒前
Qiuke发布了新的文献求助10
5秒前
5秒前
豆兼米发布了新的文献求助10
5秒前
saxon_zhang发布了新的文献求助10
5秒前
喜看财经发布了新的文献求助30
5秒前
长情完成签到,获得积分10
5秒前
希望天下0贩的0应助achilles采纳,获得10
5秒前
flawless完成签到,获得积分10
6秒前
6秒前
rhsfdfb完成签到,获得积分10
6秒前
6秒前
那时花开应助吉吉采纳,获得10
7秒前
艺二叁发布了新的文献求助10
7秒前
7秒前
7秒前
7秒前
蓝火完成签到,获得积分10
7秒前
8秒前
止兮完成签到 ,获得积分10
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
2016 Venous Blood Study (VBS) (Final V3.0) 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
从技术问题到科学问题:国家自然科学基金申请书写作指南 500
The Effective Clinical Neurologist 3ed 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7700687
求助须知:如何正确求助?哪些是违规求助? 9260034
关于积分的说明 20022530
捐赠科研通 7276362
什么是DOI,文献DOI怎么找? 3293729
关于科研通互助平台的介绍 2449395
邀请新用户注册赠送积分活动 2300326