Optimization Models Addressing Emergency Management Decisions During a Mass Casualty Incident Response

Emergency managers are often faced with the toughest decisions that can ever be made, people's lives hang in the balance. Nevertheless, these tough decisions have to be made, and made quickly. There is usually too much information to process to make the best decisions. Decision support systems can relieve a significant amount of this onus, making decision while considering the complex interweaving of constraints and resources that define the boundary of the problem. We study these complex emergency management, approaching the problem with discrete optimization. Using our operational research knowledge to model mass casualty incidents, we seek to provide solutions and insights for the emergency managers. This dissertation proposes a novel deterministic model to optimize the casualty transportation and treatment decisions in response to a MCI. This deterministic model expands on current state of the art by; (1) including multiple dynamic resources that impact the various interconnected decisions, (2) further refining a survival function to measure expected survivors, (3) defining novel objective functions that consider competing priorities, including maximizing survivors and balancing equity, and finally (4) developing a MCI response simulation that provides insights to how optimization models could be used as decision-support mechanisms.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Industrial and Systems Engineering

Department dc:contributor.department

Industrial and Systems Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2021

Author dc:creator

• Bartholomew, Paul Roche

Chair dc:contributor.committeechair

• Bish, Douglas R.

Committee members dc:contributor.committeemember

• Ellis, Kimberly P.
• Bish, Ebru K.
• Bansal, Manish

• Humanitarian logistics
• Mass casualty incidents
• Disaster response operations
• Egalitarian response metrics
• Re-optimization Simulation

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:32479

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/106667