Road network emergency accessibility planning after a major earthquake

Celso Satoshi Sakuraba, Andréa Cynthia Santos (), Christian Prins, Lucie Bouillot, Arnaud Durand and Bernard Allenbach
Additional contact information
Celso Satoshi Sakuraba: Universidade Federal de Sergipe
Andréa Cynthia Santos: Université de Technologie de Troyes
Christian Prins: Université de Technologie de Troyes
Lucie Bouillot: SERTIT, Parc d’Innovation
Arnaud Durand: SERTIT, Parc d’Innovation
Bernard Allenbach: SERTIT, Parc d’Innovation

EURO Journal on Computational Optimization, 2016, vol. 4, issue 3, No 8, 402 pages

Abstract: Abstract In the aftermath of disasters such as major earthquakes, several roads may be blocked by rubble and the population tends to search refugee in certain gathering points of the city. Road network accessibility becomes an important issue for logistic operations, specially on the first days after the quake, when the relief distribution is crucial for survival. This study focused on the Road Emergency Rehabilitation Problem, divided into the Road Network Accessibility Problem (RNAP) and the Work-troops Scheduling Problem (WSP). The first one consists in finding traversable paths for relief teams to reach the population, and the later generates a repairing schedule to improve access to refugee areas. The contributions of this study are two-fold: we present the process of transcribing satellite imagery data into graphs, and mathematical formulations for the RNAP and WSP, along with heuristics to solve the WSP. The proposed methods are able to handle large-scale graphs in an acceptable running time for real scenarios. They are tested on simulated instances and on the graph of Port-au-Prince, with more than 10,000 vertices and edges. The Port-au-Prince graph was generated from satellite images obtained by the International Charter “Space and Major Disasters” a few hours after the 2010 earthquake.

Keywords: Emergency logistics; Post-disaster relief; Network accessibility; Humanitarian logistics; Multi-flow formulations; Heuristics; 90B06 Transportation; logistics; 90B10 Network models; deterministic; 90B90 Case-oriented studies; 90C11 Mixed integer programming; 90C90 Applications of mathematical programming (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s13675-016-0070-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:eurjco:v:4:y:2016:i:3:d:10.1007_s13675-016-0070-2

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/13675

DOI: 10.1007/s13675-016-0070-2

Access Statistics for this article

EURO Journal on Computational Optimization is currently edited by Martine C. Labbé

More articles in EURO Journal on Computational Optimization from Springer, EURO - The Association of European Operational Research Societies
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().