Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30236
An Exact Algorithm for Location–Transportation Problems in Humanitarian Relief

Authors: Chansiri Singhtaun


This paper proposes a mathematical model and examines the performance of an exact algorithm for a location– transportation problems in humanitarian relief. The model determines the number and location of distribution centers in a relief network, the amount of relief supplies to be stocked at each distribution center and the vehicles to take the supplies to meet the needs of disaster victims under capacity restriction, transportation and budgetary constraints. The computational experiments are conducted on the various sizes of problems that are generated. Branch and bound algorithm is applied for these problems. The results show that this algorithm can solve problem sizes of up to three candidate locations with five demand points and one candidate location with up to twenty demand points without premature termination.

Keywords: Transportation, Disaster Response, facility location, humanitarian relief

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2012


[1] N. Altay and W. G. Green, “OR/MS research in disaster operations management,” European Journal of Operational Research, vol. 175, no. 1, pp. 475–493, 2006.
[2] B. Balcik and B. M. Beamon, “Facility location in humanitarian relief,” International Journal of Logistics Research and Applications, vol. 11, no. 2, pp. 101–12, 2008.
[3] M. Aslanzadeh, E. A. Rostami, and L. Kardar, “Logistics management and SCM in disasters,” in Supply Chain and Logistics in National, International and Governmental Environment, New York: Springer- Verlag, 2009, ch.10.
[4] A.M. Caunhye, X. Nie, and S. Pokharel, “Optimization models in emergency logistics: a literature review,” Socio-Economic Planning Sciences, vol. 46, issue 1, pp. 4-13, March 2012.
[5] R. Abounacer, M. Rekik, and J. Renaud, “An exact solution approach for multi-objective location-transportation problem for disaster response,” Computers & Operations Research, vol. 41, pp. 83–93, January 2014.