Transportation in disaster response operations
Disasters are extraordinary situations that require significant logistical deployment to transport equipment and humanitarian goods in order to help and provide relief to victims. An efficient response helps to reduce the social, economic and environmental impacts. In this paper, we define and formulate a practical transportation problem often encountered by crisis managers in emergency situations. Since optimal solutions to such a formulation may be achieved only for very small-size instances, we developed an efficient genetic algorithm to deal with realistic situations. This algorithm produces near optimal solutions in relatively short computation times and is fast enough to be used interactively in a decision-support system, providing high-quality transportation plans to emergency managers.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Tzeng, Gwo-Hshiung & Cheng, Hsin-Jung & Huang, Tsung Dow, 2007. "Multi-objective optimal planning for designing relief delivery systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 673-686, November.
- Laporte, Gilbert, 1992. "The traveling salesman problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(2), pages 231-247, June.
- Jotshi, Arun & Gong, Qiang & Batta, Rajan, 2009. "Dispatching and routing of emergency vehicles in disaster mitigation using data fusion," Socio-Economic Planning Sciences, Elsevier, vol. 43(1), pages 1-24, March.
- Hans-Ulrich Derlien & B. Guy Peters, 2008. "Introduction," Chapters,in: The State at Work, Volume 2, chapter 1 Edward Elgar Publishing.
- Balcik, Burcu & Beamon, Benita M. & Krejci, Caroline C. & Muramatsu, Kyle M. & Ramirez, Magaly, 2010. "Coordination in humanitarian relief chains: Practices, challenges and opportunities," International Journal of Production Economics, Elsevier, vol. 126(1), pages 22-34, July.
- Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
- Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
- Yi, Wei & Ozdamar, Linet, 2007. "A dynamic logistics coordination model for evacuation and support in disaster response activities," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1177-1193, June.
- Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
- Yi, Wei & Kumar, Arun, 2007. "Ant colony optimization for disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 660-672, November.
- Haghani, Ali & Oh, Sei-Chang, 1996. "Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(3), pages 231-250, May.
- Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:46:y:2012:i:1:p:23-32. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.