综合优化灾后应急响应的设施位置、伤员分配和医务人员规划

IF 3.2 Q2 MANAGEMENT
M. Oksuz, S. I. Satoglu
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引用次数: 0

摘要

目的 灾害管理和人道主义后勤(HT)在地震、洪水、飓风和海啸等大规模事件中发挥着至关重要的作用。组织良好的灾难响应对于在紧急情况下有效管理医疗中心、人员分配和伤亡分布至关重要。为解决这一问题,本研究旨在引入一个多目标随机编程模型,以加强备灾和救灾工作,重点关注地震后关键的前 72 小时。目的是优化资源、临时医疗中心和医务人员的分配,以有效拯救生命。 设计/方法/途径 本研究使用基于随机编程的动态建模和离散时间马尔可夫链来解决不确定性问题。该模型考虑了潜在的道路和医院损坏以及距离限制,并为未经治疗的伤员引入了 a 可靠性水平。该模型将最初的 72 小时分为四个时段,以捕捉地震动态。 研究结果 通过对伊斯坦布尔卡尔塔尔区的实际案例研究,证明了该模型在地震场景下的有效性。主要见解包括医疗中心的最佳位置、所需能力、必要的医务人员和伤员分配策略,所有这些对于在关键的前 72 小时内高效救灾都至关重要。 原创性/价值 这项研究创新性地将随机编程和动态建模相结合,以解决灾后医疗响应问题。针对不确定的健康状况使用马尔可夫链,并将重点放在地震发生后的第一时间,这些都具有实用价值。通过在不确定情况下优化资源分配,该研究为灾害管理和 HT 研究做出了重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated optimization of facility location, casualty allocation and medical staff planning for post-disaster emergency response
Purpose Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively. Design/methodology/approach This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics. Findings Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h. Originality/value This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.
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来源期刊
CiteScore
6.40
自引率
20.00%
发文量
20
期刊介绍: The Journal of Humanitarian Logistics and Supply Chain Management (JHLSCM) is targeted at academics and practitioners in humanitarian public and private sector organizations working on all aspects of humanitarian logistics and supply chain management. The journal promotes the exchange of knowledge, experience and new ideas between researchers and practitioners and encourages a multi-disciplinary and cross-functional approach to the resolution of problems and exploitations of opportunities within humanitarian supply chains. Contributions are encouraged from diverse disciplines (logistics, operations management, process engineering, health care, geography, management science, information technology, ethics, corporate social responsibility, disaster management, development aid, public policy) but need to have a logistics and/or supply chain focus. JHLSCM publishes state of the art research, utilizing both quantitative and qualitative approaches, in the field of humanitarian and development aid logistics and supply chain management.
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