Relief demand estimation for the emergency logistics in the aftermath of disasters

Chung-Cheng Lu, Timo Eccarius

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the aftermath of natural disasters, quick search-and-rescue operations, and efficient distribution of relief efforts and goods to affected areas are a top priority. However, it can be challenging to continuously process real-time information of differing reliability. That means, using it to estimate and predict type and extent of the demand for relief efforts. This paper proposes an approach for estimating the state of affected areas and predict associated relief demands and delivery times. The purpose is to account for data uncertainty typically arising under disaster circumstances, and to enable prompt adjustment of relief efforts in accordance with updated real-time information. The method's output can be used by decision makers to continuously optimize relief efforts. A numerical example based on the large-scale earthquake that occurred on September 21,1999 in Taiwan is presented.

Original languageEnglish
Title of host publicationTransport and Society - Proceeding of the 22nd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2017
EditorsAnthony Chen, Tony N.N. Sze
PublisherHong Kong Society for Transportation Studies Limited
Pages677-685
Number of pages9
ISBN (Electronic)9789881581464
StatePublished - 1 Jan 2017
Event22nd International Conference of Hong Kong Society for Transportation Studies: Transport and Society, HKSTS 2017 - Hong Kong, Hong Kong
Duration: 9 Dec 201711 Dec 2017

Publication series

NameTransport and Society - Proceeding of the 22nd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2017

Conference

Conference22nd International Conference of Hong Kong Society for Transportation Studies: Transport and Society, HKSTS 2017
CountryHong Kong
CityHong Kong
Period9/12/1711/12/17

Keywords

  • Disaster operations management
  • Emergency logistics
  • State estimation and relief prediction

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