Determining Evacuation Fleet Sizes for US Noncombatant Evacuation Operations in South Korea
No Thumbnail Available
Date
2019
Advisors
Journal Title
Series/Report No.
Journal ISSN
Volume Title
Publisher
Abstract
The purpose of this research is to support US noncombatant evacuation operations (NEO)
planning in South Korea and enhance an existing decision-support tool with a simulation model
that evaluates alternative resource allocations using outputs from an optimization model.
Designed in Simio, the simulation model replicates the South Korean transportation network
using nodes and timed arcs. Buses, helicopters, and trains traverse the network with various fleet
sizes and corresponding allocation of these vehicles on different pre-determined routes. Evacuees
arrive to assembly points following a stochastic time-varying arrival rate for each region. Key
outputs of interest include resource utilization, the average number of evacuees at each node, and
the total evacuation time. Multiple computational experiments analyzing the scenario of
evacuating US Department of Defense families and US government employees reveal increasing
the bus fleet size decreases the total evacuation time, with diminishing returns, until a practical
limit for the system is reached. Increasing the number of helicopters results in diminishing
returns on time saved as well, but without the performance plateau for all realistic helicopter fleet
sizes. Military planners could adopt these methods to better assess evacuation operations under
different conditions and to determine how resource allocation affects the total evacuation time in
a chaotic environment in an effort to adequately support a NEO mission in South Korea. This
research enablers planners to better capture tradeoffs between evacuation time and required
resources for the commander while providing the capacity to conduct timely what-if analysis for
operational risk assessment.
Description
Poster presented at the Summer Undergraduate Research Symposium. Affiliated with the Center for Additive Manufacturing and Logistics (CAMAL).