Positioning Disaster Relief Teams Given Dynamic Service Demand: A Hybrid Agent‐Based and Spatial Optimization Approach

Abstract

During extreme events, like hurricanes, it is essential to position relief services for non-evacuees throughout the affected region in optimal locations. While previous research has explored a variety of spatial optimization models to accomplish such a task, most work assumes that the population with demand is relatively static. However, this assumption neglects to account for potential feedbacks in the relief distribution system. For example, a population's behavior can both affect and be affected by the placement of relief services, resulting in a dynamic spatial distribution of demand. This article presents a hybrid modeling approach that utilizes GIS data with agent-based and spatial optimization models to position emergency relief teams in Bay County, Florida during a hurricane event. Non-evacuating household agents choose to remain at home or seek shelter, while relief team agents are periodically repositioned to account for changes in the spatial distribution of household agents. A total of 220 simulations are run to explore a variety of scenarios. Results show different repositioning timing strategies and the magnitude of the feedback effect drastically changes the level of access households have to relief teams. Ultimately, this work demonstrates the importance of accounting for behavioral and spatial dynamics in disaster relief distribution systems.

An Innovation Approach for Optimal Resource Allocation in Emergency Management

“…In [12], Hawe et al introduced an agent-based emergency simulation system for a two-site major incident, in which a centralised control simulator was used to coordinate all resources (vehicle agents) from different emergency services and optimise the allocation result based on time. In [29], Widener et al proposed a hybrid agent-based I E E E P r o o f optimisation approach of positioning relief teams for largescale disaster to assist local residents, in which p-median optimisation model is used to select the p best relief team locations based on the given positions of all trapped residents and candidate shelters. Apart from agent-based approaches, there are other promising centralised approaches have been proposed to optimise emergency resource allocation plans.…”

“…Nevertheless, we should not neglect the shortcomings of using centralised approaches in emergency management. For example, the approaches proposed by Lam et al [7], Widener et al, Hawe et al [12] and [29] were designed to optimise the resource allocation for large-scale emergency events with global information. However, in real-world situations, such large-scale emergency situations usually required different types of resources from different emergency departments or companies.…”

Dynamic Resource Scheduling in Emergency Environment

“…Some researches focus on resource allocation approaches from centralization to decentralization. For example, the approaches proposed by Chou et al [Chou, Tsai, Chen et al (2014)], Widener et al [Hawe, Coates, Wilson et al (2015); Widener, Horner et al (2015)] were designed to optimize the resource allocation for largescale emergency events with global information. In Zhang et al [Zhang, Zhang, Ren et al (2016)], Zhang et al proposed a distributed resource allocation method based on multiagent, which used the domain transmission theory to deal with emergencies, and effectively solved the problem of deploying the corresponding planning arrangement in the absence of appropriate resources with global information by considering the time severity level.…”

Unintended Feedbacks: Challenges and Opportunities for Improving Conservation Effectiveness

“…Systems dynamics modeling has been applied to manage and avoid unintended consequences and their feedbacks in designing hazards management and disaster relief policy (Gillespie et al 2004). For example forest fire management (Collins et al 2013), emergency resource coordination (Wang et al 2010), and efficient positioning of relief services (Widener et al 2015). Clearly articulated with systems thinking theory, the SES literature is where most of the work on human-natural systems has been done, providing a strong grounding for work on unintended feedbacks.…”