Simulating distribution of emergency relief supplies for disaster response operations

Lee, Myeong Soo; Ghosh,; Ettl,

doi:10.1109/wsc.2009.5429246

Cited by 32 publications

(16 citation statements)

References 19 publications

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“…Computational simulations, particularly agent-based simulations, are the predominant approach in the computing literature to predict the consequences of certain courses of action in disasters [22], to model information flow among first responders [49], to model the logistic distribution of emergency relief supplies [32]. However, as hinted above, these simulations are a poor substitute for real-world field trials.…”

Section: Disaster Simulation and Gamesmentioning

confidence: 99%

Human–agent collaboration for disaster response

Ramchurn

Jiang

et al. 2015

Auton Agent Multi-Agent Syst

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In the aftermath of major disasters, first responders are typically overwhelmed with large numbers of, spatially distributed, search and rescue tasks, each with their own requirements. Moreover, responders have to operate in highly uncertain and dynamic environments where new tasks may appear and hazards may be spreading across the disaster space. Hence, rescue missions may need to be re-planned as new information comes in, tasks are completed, or new hazards are discovered. Finding an optimal allocation of resources to complete all the tasks is a major computational challenge. In this paper, we use decision theoretic techniques to solve the task allocation problem posed by emergency response planning and then deploy our solution as part of an agent-based planning tool in real-world field trials. By so doing, we are able to study the interactional issues that arise when humans are guided by an agent. Specifically, we develop an algorithm, based on a multi-agent Markov decision process representation of the task allocation problem and show that it outperforms standard baseline solutions. We then integrate the algorithm into a planning agent that responds to requests for tasks from participants in a mixed-reality location-based game, called AtomicOrchid, that simulates disaster response settings in the real-world. We then run a number of trials of our planning agent and compare it against a purely human driven system. Our analysis of these trials show that human commanders adapt to the planning agent by taking on a more supervisory role and that, by providing humans with the flexibility of requesting plans from the agent, allows them to perform more tasks more efficiently than using purely human interactions to allocate tasks. We also discuss how such flexibility could lead to poor performance if left unchecked.

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Section: Disaster Simulation and Gamesmentioning

confidence: 99%

Human–agent collaboration for disaster response

Ramchurn

Jiang

et al. 2015

Auton Agent Multi-Agent Syst

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“…First, we determine the consumption and delivery values for these commodities based on the experiences in the aftermath of Sandy. To begin, we assume that 10,000 people needed food and medicine in a specific area within the affected region, where it is assumed that for each day at a distribution center or shelter, each person is given, on average, 2 MRE's (Meal Ready-to-eat) and ½ units of medicine (Lee et al, 2011). Second, in the aftermath of super storm Sandy, IAP Worldwide Services was tasked with the installation and operation of approximately 1000 generators throughout New Jersey, New York, Pennsylvania and Massachusetts (IAP, 2012).…”

Section: Case Studymentioning

confidence: 99%

“…These values are created by the 2 MRE's and ½ medicine assumption given in (Lee et al, 2011) and based on the vital supplies delivered during the emergency operations conducted by the Louisiana National Guard.…”

Section: Case Studymentioning

confidence: 99%

An RFID-based inventory management framework for emergency relief operations

Özgüven

Özbay

2015

Transportation Research Part C: Emerging Technologies

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“…Under this scenario, it is assumed that 10,000 people are gathered in the Superdome, where two MREs and one-half unit of medicine are assumed to be given per person per day, on average (38). Depending on the strength of the hurricane, demand occurs at five levels u, where 1 represents the lowest demand and 5 represents the highest.…”

Section: Case Study 1 (Base Case) Change In Severity Of Disastermentioning

confidence: 99%

“…• Expected total delivery and total consumption values are created by the two MREs and one-half unit of medicine assumption given previously (38) Delivery and consumption values are used to calculate the mean, variance, and covariance matrix for the distribution of the vital supplies. The results are given in Table 4.…”

Section: Case Study 1 (Base Case) Change In Severity Of Disastermentioning

confidence: 99%

Case Study–Based Evaluation of Stochastic Multicommodity Emergency Inventory Management Model

Özgüven

Özbay

2012

Transportation Research Record

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reduce the harm and alleviate the suffering that these disasters cause their victims (2). A significant component of emergency disaster logistics is to satisfy the vital needs of the people located in emergency shelters, such as the Superdome in New Orleans, Louisiana, which was used a shelter during Hurricane Katrina. Holguin-Veras et al. stated that the lack of an efficient humanitarian inventory control model caused major negative consequences for the victims after Hurricane Katrina (3). Therefore, disaster planners and engineers should find a way to reduce the uncertainties associated with emergency operations, to calculate the expected costs of delivery and consumption processes throughout these operations, and to manage the availability and distribution of vital resources. With these requirements, stocking of an inventory of vital supplies becomes a must to facilitate the rapid mobilization of available resources during emergency operations. Therefore, a case-based analysis of a humanitarian inventory management model needs to be developed before the occurrence of a catastrophe. Such an analysis can determine the safety stock levels and prevent possible disruptions at minimal cost for different scenarios.This paper demonstrates the importance of an efficient humanitarian inventory management system through the use of realistic case studies built with information available from past disasters. A humanitarian inventory management system should be robust against disruptions to minimize the impacts of disasters on the supply and consumption of vital commodities. The ultimate goal is to use realistic case studies to emphasize this simple yet important requirement. Case-Based emergenCy Inventory managementDisasters are extreme, unexpected events that often occur with little or no warning and that make people acutely aware of their vulnerabilities. Table 1 shows the worldwide distribution of disasters that took place between 1900 and 2011. The data were taken from the Emergency Disaster Database provided by the Centre for Research on the Epidemiology of Disasters (4).The difficulty with the handling of emergency operations differs for each type of disaster. Therefore, an efficient inventory management system should be capable of handling different types of disasters with distinct characteristics. To address these different characteristics, a case-based emergency inventory management problem is introduced within a disaster framework. Planners and engineers first seek a number of objectives to obtain an efficient emergency inventory management methodology. These objectives differ from those of Emergency disaster management has emerged as a vital tool for reducing the harm and alleviating the suffering that disasters worldwide cause their victims. A significant task of planners involved in emergency disaster management is the ability to plan for and satisfy the vital needs of the people located in emergency shelters, such as the Superdome in New Orleans, Louisiana, which was used as a shelter during Hurricane Katrina...

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Simulating distribution of emergency relief supplies for disaster response operations

Cited by 32 publications

References 19 publications

Human–agent collaboration for disaster response

Human–agent collaboration for disaster response

An RFID-based inventory management framework for emergency relief operations

Case Study–Based Evaluation of Stochastic Multicommodity Emergency Inventory Management Model

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