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Preliminary Evaluation of Multi-criteria Decision-Making Methodology for Emergency Management

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Advances in Human Factors and System Interactions (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 265))

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Abstract

Decision-making related to emergencies and disasters is a daunting process given the dynamic and complex nature of such events, the wide range of factors to manage, and the large amount of information to consider. To address the challenge, the long-term goals of this work advocate for the use of an adaptive intelligent system to assist with these complex decision tasks. This paper provides background for MCDM methods and their uses and develops and proposes a taxonomy of eleven questions for use in selecting MCDM methods within complex decision-making environments such as emergency management.

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Acknowledgments

Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-19-2-0062. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

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Authors and Affiliations

  1. Towson University, Towson, MD, USA

    Justine P. Caylor & Robert J. Hammell II

  2. US Army Research Laboratory, Aberdeen Proving Ground, MD, USA

    Adrienne J. Raglin

Authors
  1. Justine P. Caylor
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  2. Robert J. Hammell II
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  3. Adrienne J. Raglin
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Correspondence to Justine P. Caylor .

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  1. Faculty of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal

    Isabel L. Nunes

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Caylor, J.P., Hammell, R.J., Raglin, A.J. (2021). Preliminary Evaluation of Multi-criteria Decision-Making Methodology for Emergency Management. In: Nunes, I.L. (eds) Advances in Human Factors and System Interactions. AHFE 2021. Lecture Notes in Networks and Systems, vol 265. Springer, Cham. https://doi.org/10.1007/978-3-030-79816-1_2

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  • DOI: https://doi.org/10.1007/978-3-030-79816-1_2

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