Collaborative Vehicle Dispatching for Resilient and Fair Emergency Response

Yuying Long, Ying Sun, Gangyan Xu, Pengfeng Shu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Efficient emergency vehicle dispatching is crucial for emergency response and could reduce human casualties and economic losses. However, during large scale unconventional disasters, rescue demands increase dramatically that traditional vehicle dispatching method cannot well cope with the unbal-anced situation, thus bringing about delayed response, uneven treatment, and waste of resources. To address these problems, this paper proposes an effective emergency vehicle dispatching method for resilient and fair emergency response. Firstly, a dy-namic emergency vehicle dispatching model is built considering resilience and fairness. Then a collaborative vehicle dispatching method with Tabu Search-based dispatching algorithm is pro-posed to solve the model. Finally, a simulation case study is carried out to verify the performance of the proposed method.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages649-653
Number of pages5
ISBN (Electronic)9781665437714
DOIs
Publication statusPublished - Dec 2021
Event2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 - Virtual, Online, Singapore
Duration: 13 Dec 202116 Dec 2021

Publication series

Name2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

Conference

Conference2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Country/TerritorySingapore
CityVirtual, Online
Period13/12/2116/12/21

Keywords

  • Collaborative vehicle dis-patching
  • Emergency response
  • Fairness
  • Resilience
  • Tabu search

ASJC Scopus subject areas

  • Strategy and Management
  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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