Modeling emergency response operations: A theory building survey

J. P. Minas, N. C. Simpson, Z. Y. Tacheva

Research output: Contribution to journalReview articlepeer-review

Abstract

During the response phase of an emergency, decision makers manage processes that save lives, protect infrastructure and contain evolving threats. In this paper, we undertake a comprehensive survey of the emergency response operations literature. In collating and classifying our literature sample, we employ novel methodologies adapted from unsupervised learning and network analysis to reduce sampling and expectancy biases. We find that operations research supporting emergency response has been developing in discernible clusters, with each cluster of studies focused on a particular process such as evacuation or aid distribution. Our study both serves to strengthen the theoretical foundation of emergency response operations and identifies plentiful opportunities for researchers seeking to advance the state-of-the-art in this exciting frontier of operations research.

Original languageEnglish (US)
Article number104921
JournalComputers and Operations Research
Volume119
DOIs
StatePublished - Jul 2020
Externally publishedYes

Keywords

  • Citation analysis
  • Disaster management
  • Emergency response
  • Literature survey
  • Unsupervised learning

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research

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