Pre-positioning of emergency supplies for disaster response

Pre-positioning of emergency supplies for disaster response Pre-positioning of emergency supplies is one mechanism of increasing preparedness for natural disasters. The goal of this research is to develop an emergency response planning tool that determines the location and quantities of various types of emergency supplies to be pre-positioned, under uncertainty about if, or where, a natural disaster will occur. The paper presents a two-stage stochastic mixed integer program (SMIP) that provides an emergency response pre-positioning strategy for hurricanes or other disaster threats. The SMIP is a robust model that considers uncertainty in demand for the stocked supplies as well as uncertainty regarding transportation network availability after an event. Due to the computational complexity of the problem, a heuristic algorithm referred to as the Lagrangian L-shaped method (LLSM) is developed to solve large-scale instances of the problem. A case study focused on hurricane threat in the Gulf Coast area of the US illustrates application of the model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transportation Research Part B: Methodological Elsevier

Pre-positioning of emergency supplies for disaster response

Loading next page...
 
/lp/elsevier/pre-positioning-of-emergency-supplies-for-disaster-response-iSBXaErH4t
Publisher
Elsevier
Copyright
Copyright © 2009 Elsevier Ltd
ISSN
0191-2615
eISSN
1879-2367
DOI
10.1016/j.trb.2009.08.003
Publisher site
See Article on Publisher Site

Abstract

Pre-positioning of emergency supplies is one mechanism of increasing preparedness for natural disasters. The goal of this research is to develop an emergency response planning tool that determines the location and quantities of various types of emergency supplies to be pre-positioned, under uncertainty about if, or where, a natural disaster will occur. The paper presents a two-stage stochastic mixed integer program (SMIP) that provides an emergency response pre-positioning strategy for hurricanes or other disaster threats. The SMIP is a robust model that considers uncertainty in demand for the stocked supplies as well as uncertainty regarding transportation network availability after an event. Due to the computational complexity of the problem, a heuristic algorithm referred to as the Lagrangian L-shaped method (LLSM) is developed to solve large-scale instances of the problem. A case study focused on hurricane threat in the Gulf Coast area of the US illustrates application of the model.

Journal

Transportation Research Part B: MethodologicalElsevier

Published: May 1, 2010

References

  • New vision of emergency response planning
    Al-qurashi, F.
  • Optimized resource allocation for emergency response after earthquake disasters
    Fiedrich, F.; Gehbauer, F.; Rickers, U.
  • Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations
    Haghani, A.; Oh, S.-C.
  • Emergency logistics planning in natural disasters
    Ozdamar, L.; Ekinci, E.; Kucukyazici, B.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off