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Scheduling the airlift of relief supplies into a damaged or small airport during a crisis is complex yet crucial. The volume of cargo and flights can temporarily overwhelm the airport’s capacity and the mix of flights adds complexity. The purpose of this paper is to better characterize airport operations during a crisis, to develop a model that can assess strategies for scheduling flights and to draw implications for decision makers.

First, empirical data are analyzed to characterize airport operations. Previously unreported data from the 2010 Haiti earthquake response in the form of a “flight log” are analyzed to provide new insights and parameters. Alternate scheduling strategies are drawn from review of the literature and After Action Reports. Second, a queuing model is developed to understand operations in past crises and predict the impact of alternate scheduling strategies. Empirical data provide the parameters for airport scenarios evaluated.

Unloading capacity is seen to be the bottleneck but also to not be fully utilized, suggesting that a more aggressive flight schedule is needed. Scheduling flights is shown to be a tradeoff between volume of aid delivered and flights that must be diverted. The proper mix of aircraft and prioritized divert policies also provide benefits. Finally, it is beneficial, though perhaps counterintuitive, to create a parking buffer upstream from the unloading bottleneck.

Analysis of previously unreported data from the Haiti earthquake provides new insights regarding airport parking and unloading operations. A new model of airport scheduling for disaster response is proposed. The model differs from other humanitarian airlift models in that it focuses on aircraft parking and unloading. It differs from commercial aircraft scheduling and gate assignment in the objective used.

The COVID-19 pandemic has forced countries to consider how to reach vulnerable communities with extended outreach services to improve vaccination uptake. The authors created an optimization model to align with decision-makers' objective to maximize immunization coverage within constrained budgets and deploy resources considering empirical data and endogenous demand.

A mixed integer program (MIP) determines the location of outreach sites and the resource deployment across health centers and outreach sites. The authors validated the model and evaluated the approach in consultation with UNICEF using a case study from The Gambia.

Results in The Gambia showed that by opening new outreach sites and optimizing resource allocation and scheduling, the Ministry of Health could increase immunization coverage from 91.0 to 97.1% under the same budget. Case study solutions informed managerial insights to drive gains in vaccine coverage even without the application of sophisticated tools.

The research extended resource constrained LMIC vaccine distribution modeling literature in two ways: first, endogenous calculation of demand as a function of distance to health facility location enabled the effective design of the vaccine network around convenience to the community and second, the model's resource bundle concept more accurately and flexibly represented complex requirements and costs for specific resources, which facilitated buy-in from stakeholders responsible for managing health budgets. The paper also demonstrated how to leverage empirical research and spatial analysis of publicly available demographic and geographic data to effectively represent important contextual factors.

The purpose of the paper is to deepen the understanding of supply chain performance objectives in the humanitarian context by striving to understand the underlying goals and conceptual variables behind the measurement of performance, such as efficiency.

The research is an in-depth case study with one humanitarian organization. The data are gathered with mixed methods over a two-year period. Interviews were conducted in August 2010 and April 2012, and a survey conducted in October 2012.

Misalignments are detected among different groups in humanitarian operations and between their goals and processes. These misalignments could possibly be corrected through long-term thinking in short-term operations by considering sustainability aspects throughout humanitarian assistance, for example. In addition, efficiency was a commonly identified objective in the case organization, although the definition varied widely and extended beyond the traditional definition of productivity to include planning, accountability and quality.

Better communication and definition of terms is necessary to align goals and the power hierarchy in humanitarian supply chains, where operations seem to be structured more according to donor requirements then beneficiary needs.

This is an in-depth case study, applying goal-setting theory to study supply chain performance. The study further responds to the public “aid efficiency” discussion by striving to recognize how efficiency is understood and how it can be measured in a humanitarian supply chain.

The purpose of this paper is to describe and analyze a successful training exercise in detail, through both a practical and a theoretical lens, in order to identify critical aspects of its success and enable others to build upon it; and to capture insights and lessons learned in a framework that will facilitate the design of future trainings for a variety of goals and audiences.

The authors document and analyze the case study of a successful humanitarian logistics training exercise: the World Food Programme’s Logistics Response Team (WFP’s LRT) training. The LRT is described in detail in order to capture the extensive knowledge and experience that went into developing the full-scale, immersive exercise.

The authors evaluate the LRT training through a theoretical lens, considering how it teaches the diverse set of skills required and identifying reasons for its success. The authors contrast the LRT with a light version developed for classroom use, and capture insights in a framework that highlights critical aspects of training design.

The requirements and design aspects highlighted in the framework are very high level, but they focus attention on key aspects that should be considered. Future research should develop more targeted metrics for evaluating what people learn from training exercises. More generally, a systematic approach to capturing knowledge and codifying good practices should be developed.

The detailed case study and framework provide a basis for the design and improvement of simulated emergency training exercises, which are common in the humanitarian practice community.

The case study of WFP’s LRT training formally documents valuable knowledge and experience that went into its development. The humanitarian community can use the proposed framework to more systematically evaluate, improve, and extend training exercises.