A robust optimization approach to volunteer management in humanitarian crises

Lassiter, Kyle; Khademi, Amin; Taaffe, Kevin

doi:10.1016/j.ijpe.2015.02.018

Cited by 56 publications

(43 citation statements)

References 30 publications

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“…, Lassiter et al. , ). Instead, we are interested in studying the setting in which agents are heterogeneous in their experience and their arrivals can lead to congestion in the storehouse, which is typical during disaster response.…”

Section: Simulation Studymentioning

confidence: 99%

“…Research on volunteer experience focuses on disaster settings when the needs of the population, the availability of volunteers and their skills change over time. Lassiter et al (2014Lassiter et al ( , 2015 develop multi-criteria optimization models to minimize unmet task demand and maximize volunteer assignment preferences while accounting for the volunteers' experience, the experience required for the task, volunteer training opportunities and volunteer attrition. They find that optimal strategies for organizations include training inexperienced volunteers at the very beginning of disasters and matching volunteer preferences only up to a certain threshold.…”

Section: Volunteer Experiencementioning

confidence: 99%

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Volunteer Management in Charity Storehouses: Experience, Congestion and Operational Performance

Urrea

Pedraza‐Martinez

Besiou

2019

Production and Operations Management

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We study volunteer management at a charity storehouse operated by a large faith‐based organization. The storehouse runs entirely on volunteer efforts. We investigate the role of volunteer experience and storehouse congestion in the preparation of orders using a multi‐method approach. First, we conduct a field study to explore these relationships and collect data at the level of volunteers’ teams. These teams can pair volunteers with either different levels of experience (mixed pairing) or equal levels of experience (no‐mixed pairing). Second, we estimate the effects of volunteer experience and storehouse congestion on the order processing times empirically. Third, we build a simulation model to study how operational decisions—volunteers’ pairing in teams and whether to allow or impede storehouse congestion—affect two performance metrics: on‐time order preparation rate and additional time to prepare the orders, in steady conditions. Then, we simulate disaster conditions at the storehouse, that is, simultaneous surges in supply of volunteers and demand of orders. Contrary to extant literature on team collaboration, we find that no‐mixed pairing outperforms mixed pairing under disaster conditions with storehouse congestion. In fact, no‐mixed pairing improves the on‐time order preparation by 4.32% and the additional time to prepare the orders by 14.42% compared to mixed pairing. Moreover, under disaster conditions, a “controlled congestion” policy at the storehouse delivers the best performance metrics.

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Section: Simulation Studymentioning

confidence: 99%

Section: Volunteer Experiencementioning

confidence: 99%

Volunteer Management in Charity Storehouses: Experience, Congestion and Operational Performance

Urrea

Pedraza‐Martinez

Besiou

2019

Production and Operations Management

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“…There are only a limited number of papers that focus on volunteer scheduling and DOM. Other than the three papers discussed at the beginning of this section (Abualkhair et al 2020, Mayorga et al 2017, Paret et al 2020, the only other studies to examine volunteer scheduling from a DOM perspective are Falasca and Zobel (2012), Lassiter et al (2015), and Urrea et al (2019). However, systematic scheduling of volunteer labor has been considered in other settings; an annual folk music festival (Gordon and Erkut 2004), reviewer assignments for an academic conference (Sampson 2006), and a bike sharing program (Kaspari 2010).…”

Section: Disaster Operations Management and Volunteer Schedulingmentioning

confidence: 99%

“…Another characteristic that is likely to be more pronounced in DOM than in other VLA contexts is the degree of task uncertainty. Lassiter et al (2015) accommodate task uncertainty by proposing a robust optimization framework that seeks to minimize unmet task demands. Lastly, VLA in DOM is often characterized by a large number of unaffiliated volunteers who lack training and experience, and a smaller number of experienced volunteers who are affiliated with official responding agencies.…”

Section: Disaster Operations Management and Volunteer Schedulingmentioning

confidence: 99%

Optimal Control of Parallel Queues for Managing Volunteer Convergence

Zayas‐Cabán

Lodree

Kaufman

2020

Production and Operations Management

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V olunteer convergence refers to the influx of volunteers to affected areas after large-scale disasters. There are not only many benefits to volunteer convergence, but it also creates significant logistical challenges that can impede relief efforts. This study examines polices for admitting volunteers into organized relief operations, and for assigning admitted volunteers to relief tasks. We represent this problem as a queueing system where, in addition to customer arrivals and departures, random server arrivals and abandonments are also present. Then, using a Markov decision process framework, we analyze server admission and assignment policies that seek to minimize relief tasks holding costs as well as volunteer holding and rejection costs. We show that the classic cl rule, a server allocation policy that determines where to put servers based on relief tasks holding costs and processing requirements, is optimal under both collaborative and noncollaborative service regimes and when batch server arrivals are allowed. Additionally, we find that the optimal server admission policy is a complex state-dependent policy. As a result, we propose a class of admission heuristics that depend on the number of workers in the system and the remaining system workload. In a numerical study, we show that our heuristic policies perform well with respect to long-run average costs, waiting times, number of volunteers in the system, and number of volunteers idling in the system over a range of parameter values and distributions that are based on real data from a case study. As such, they promise volunteer coordinators an effective and simple way to manage disaster volunteers.

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“…Así, la fase de respuesta inicia inmediatamente acontece el desastre, con actividades como: búsqueda y rescate de personas, recolección de información sobre el área del desastre, identificación de los sitios apropiados para los refugios, determinación de rutas de evacuación, transporte y entrega de suministros de emergencia (Tzeng, et al, 2007;Holguín-Veras, et al, 2013). El objetivo es la preservación de la vida, las instalaciones, el ambiente, y la estructura social, econó-mica y política de la comunidad, mientras se busca tener eficiencia en las operaciones (Altay & Green, 2006;Lassiter, et al, 2015). Según Rottkemper, et al (2011), la transición entre las etapas de respuesta y recuperación se hace de forma gradual.…”

Section: Introductionunclassified

Gestión de la logística humanitaria en las etapas previas al desastre: revisión sistemática de la literatura

López-Vargas

Cárdenas-Aguirre

2017

rev. investig. desarro. innov

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Cómo citar este artículo: López-Vargas, J. C., & Cárdenas-Aguirre, D. M. (2017) Gestión de la logística humanitaria en las etapas previas al desastre:revisión sistemática de la literatura. Rev.investig.desarro.innov, 7(2), 203-216. doi: 10.19053/20278306.v7.n2.2017 ResumenEl objetivo de este trabajo es analizar la forma en que las etapas de mitigación y preparación que hacen parte del proceso de la logística humanitaria son presentadas en la literatura relacionada con el tema. Para esto, se realizó una revisión sistemática de la literatura con el uso de la aplicación Tree of Science de la Universidad Nacional de Colombia -Sede Manizales. La revisión permite reconocer la importancia que estas etapas tienen respecto al nivel de respuesta ante los desastres, así como los tipos de desastres y las decisiones de mitigación y preparación que más comúnmente se abordan. Asimismo, se pone en evidencia una menor participación de estos temas en la literatura especializada. Por lo tanto, ampliar el estudio de las etapas de mitigación y preparación hacia otros tipos de desastres y en otros contextos geográfi-cos, constituye un campo de interés para futuras investigaciones.Palabras clave: logística humanitaria, Tree of Science, mitigación de desastres, preparación de desastres. AbstractThe aim of this paper is to analyze how mitigation and preparedness stages that are part of the process of humanitarian logistics are presented in the literature related with the topic. For this, a systematic review of the literature was conducted using application Tree of Science of the Universidad Nacional de Colombia in Manizales. The review allows recognize the importance that these stages have on the level of disaster response, as well as the types of disasters and mitigation and preparation decisions most commonly addressed. Likewise, a smaller participation of these topics is evidenced in the specialized literature. Therefore, extend the study of the stages of mitigation and preparedness to other types of disasters and other geographical contexts is a field of interest for future research.

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A robust optimization approach to volunteer management in humanitarian crises

Cited by 56 publications

References 30 publications

Volunteer Management in Charity Storehouses: Experience, Congestion and Operational Performance

Volunteer Management in Charity Storehouses: Experience, Congestion and Operational Performance

Optimal Control of Parallel Queues for Managing Volunteer Convergence

Gestión de la logística humanitaria en las etapas previas al desastre: revisión sistemática de la literatura

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