Protecting vulnerable people during pandemics through home delivery of essential supplies: a distribution logistics model

IF 3.2 Q2 MANAGEMENT
E. Breitbarth, Wendelin Groβ, Alexander Zienau
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引用次数: 13

Abstract

PurposeThis paper studies a concept for protecting vulnerable population groups during pandemics using direct home deliveries of essential supplies, from a distribution logistics perspective. The purpose of this paper is to evaluate feasible and resource-efficient home delivery strategies, including collaboration between retailers and logistics service providers based on a practical application.Design/methodology/approachA food home delivery concept in urban areas during pandemics is mathematically modeled. All seniors living in a district of Berlin, Germany, represent the vulnerable population supplied by a grocery distribution center. A capacitated vehicle routing problem (CVRP) is developed in combination with a k-means clustering algorithm. To manage this large-scale problem efficiently, mixed-integer programming (MIP) is used. The impact of collaboration and additional delivery scenarios is examined with a sensitivity analysis.FindingsRoughly 45 medically vulnerable persons can be served by one delivery vehicle in the baseline scenario. Operational measures allow a drastic decrease in required resources by reducing service quality. In this way, home delivery for the vulnerable population of Berlin can be achieved. This requires collaboration between grocery and parcel services and public authorities as well as overcoming accompanying challenges.Originality/valueDeveloping a home delivery concept for providing essential goods to urban vulnerable groups during pandemics creates a special value. Setting a large-scale CVRP with variable fleet size in combination with a clustering algorithm contributes to the originality.
在流行病期间通过送货上门保护弱势人群:一种配送物流模式
本文从配送物流的角度研究了流行病期间使用基本物资直接送货上门保护弱势群体的概念。本文的目的是评估可行的和资源高效的送货到家策略,包括零售商和物流服务提供商之间的合作,基于一个实际应用。设计/方法/方法对流行病期间城市地区的食品送货上门概念进行了数学建模。居住在德国柏林某地区的所有老年人都是由食品杂货配送中心供应的弱势群体。结合k均值聚类算法,提出了一种有能力车辆路径问题。为了有效地管理这一大规模问题,采用了混合整数规划(MIP)。通过敏感性分析检查协作和其他交付场景的影响。调查结果在基线情况下,一辆运载工具可以为大约45名医疗上脆弱的人提供服务。操作措施可以通过降低服务质量来大幅减少所需资源。通过这种方式,可以实现柏林弱势群体的送货上门。这需要杂货和包裹服务与公共当局之间的合作,以及克服随之而来的挑战。创意/价值在大流行期间为城市弱势群体提供必需品的送货上门概念创造了特殊价值。结合聚类算法,设置可变车队规模的大规模CVRP,具有独创性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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