Skip to main content

A Network Transshipment Model for Planning Humanitarian Relief Operations After a Natural Disaster

  • Chapter
  • First Online:
Book cover Decision Aid Models for Disaster Management and Emergencies

Part of the book series: Atlantis Computational Intelligence Systems ((ATLANTISCIS,volume 7))

Abstract

Every year, natural disasters and humanitarian crises affect approximately 200 million people, requiring the quick movement of goods and people to ease the human suffering and to return the population to some sense of normality. With contributions to humanitarian relief programmes falling short of what is required, programme managers need to become more cost-efficient and do more with less. The field of operational research (OR) has developed many models to help the commercial sector examine current practices and find ways of becoming more cost efficient. However, much of this good practice has not transferred to the humanitarian field. This paper develops a mathematical transshipment multi-commodity supply-chain flow model for use within humanitarian relief operations. A small data set, based on real life data from the South Asian Earthquake of October 2005, is used to validate the model solutions compared to the real life situation. Several variants of the model are developed to add realism and flexibility over a number of possible scenarios. From the variant solutions several recommendations are made to provide guidance on planning for humanitarian relief operations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Altay, N. and Green, W. G. (2006). OR/MS research in disaster operations management, European Journal of Operational Research 175, 1, pp. 475–493.

    Google Scholar 

  2. Balcik, B., Beamon, B. M., Krejci, C. C., Muramatsu, K. M. and Ramirez, M. (2010). Coordination in humanitarian relief chains: Practices, challenges and opportunities, International Journal of Production Economics 126, 1, pp. 22–34, Improving Disaster Supply Chain Management - Key supply chain factors for humanitarian relief.

    Google Scholar 

  3. Barbaroso˘glu, G. and Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response, Journal of the Operational Research Society 55, pp. 45–53.

    Google Scholar 

  4. Beamon, B. and Kotleba, S. (2006). Inventory modelling for complex emergencies in humanitarian relief operations, International Journal of Logistics: Research and Applications 9, 1, pp. 1–18.

    Google Scholar 

  5. Beamon, B. M. (2004). Humanitarian relief chains: issues and challenges, in Proceedings of the 34th International Conference on Computers and Industrial Engineering (San Francisco, CA), pp. 77–82.

    Google Scholar 

  6. Brown, G., Keegan, J., Vigus, B. and Wood, K. (2001). The Kellogg company optimizes production, inventory, and distribution, Interfaces 31, 6, pp. 1–15.

    Google Scholar 

  7. Camm, J. D., Chorman, T. E., Dill, F. A., Sweeney, D. J. and WWegbyn, G. (1997). Blending OR/MS, judgment, and GIS: Restructuring P&G’s supply chain operations, Interfaces 27, 1, pp. 128–142.

    Google Scholar 

  8. Caunhyea, A. M., Niea, X. and Pokharel, S. (2012). Optimization models in emergency logistics: A literature review, Socio-Economics Planning Sciences 46, 1, pp. 4–13.

    Google Scholar 

  9. Clark, A. R. (2011). Humanitarian supply chain network models for disaster relief, LANDTRANSLOG II Workshop, Puerto Varas, Chile, 12-15 December 2011, http://www.cems.uwe.ac.uk/~arclark, accessed 11 April 2012.

  10. Ergott, M. and Gandibleux, X. (2002). Multiobjective combinatorial optimization - theory, methodology and applications, International Series in Operational Research and Management Science 52, pp. 369–444.

    Google Scholar 

  11. Erhgott, M. and Gandibleux, X. (2002). emphMultiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys, Vol. 52 (Kluwer).

    Google Scholar 

  12. Fourer, R., Gay, D. and Kernighan, B. (2003). emphA Mathematical Programming Language, 2nd edn. (Thomson, Calif, USA).

    Google Scholar 

  13. Fritz Institute (2005). Logistics and the effective delivery of humanitarian relief, www.fritzinstitute.org, accessed 11 April 2012.

  14. Goodwin, P. and Wright, G. (2004). emphDecision Analysis for Management Judgement, 3rd edn. (Wiley, Chichester).

    Google Scholar 

  15. Graves, S. C. and Willems, S. P. (2000). Optimizing strategic safety stock placement in supply chains, Manufacturing & Service Operations Management 2, 1, pp. 68–83.

    Google Scholar 

  16. Haghani, A. and Oh, S. (1996). Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations, Transport Research - Part A 30, 3, pp. 231–250

    Google Scholar 

  17. Hwang, H. (1999). A food distribution model for famine relief, Computers and Industrial Engineering 37, pp. 335–338.

    Google Scholar 

  18. Ilog (2004). emphCPLEX 9.1 User’s Manual, ILOG S.A, www.cplex.com.

  19. IRFC (1994a). International federation of the red cross and red crescent, code of conduct, www.ifrc.org, accessed 11 April 2012.

  20. IRFC (1994b). International federation of the red cross and red crescent, code of conduct: Annex 1, www.ifrc.org, accessed 11 April 2012.

  21. IRFC (2006). International federation of the red cross and red crescent, disasters, www.ifrc.org, accessed 11 April 2012.

  22. Long, D. (2003). emphInternational Logistics: Global Supply Chain Management (Kluwer Academic Publishers, Massachusetts).

    Google Scholar 

  23. Long, D. and Wood, D. (1995). The logistics of famine relief, Journal of Business Logistics 16, 1, pp. 213–229.

    Google Scholar 

  24. M T Melo, S. N. and da Gama, F. S. (2005). Dynamic multi-commodity capacitated facility location: a mathematical modelling framework for strategic supply chain planning, Computers and Operations Research 33, pp. 181–208.

    Google Scholar 

  25. Martin, R. (2005). The balancing act: Speed, agility versus cost in effective disruption management, http://www.itconversations.com, podcast accessed 11 April 2012.

  26. McGuire, G. (2000). Supply chain management in the context of international humanitarian assistance in complex emergencies – part 1, Supply Chain Practice 2, 4, pp. 30–43.

    Google Scholar 

  27. McGuire, G. (2001). Supply chain management in the context of international humanitarian assistance in complex emergencies – part 2, Supply Chain Practice 3, 1, pp. 4–18.

    Google Scholar 

  28. Oloruntoba, R. and Gray, R. (2005). Humanitarian aid: an agile supply chain? Supply Chain Management 11, 2, pp. 115–120.

    Google Scholar 

  29. Ortuño, M., Tirado, G. and Vitoriano, B. (2011). A lexicographical goal programming based decision support system for logistics of humanitarian aid, TOP: An Official Journal of the Spanish Society of Statistics and Operations Research 19, 2, pp. 464–479.

    Google Scholar 

  30. Ozdamar, L. (2011). Planning helicopter logistics in disaster relief, OR Spektrum 33, 3, p. 655–672.

    Google Scholar 

  31. Ozdamar, L., Ekinci, E. and Kucukyazici, B. (2004). Emergency logistics planning in natural disasters, Annals of Operations Research 129, pp. 217–245.

    Google Scholar 

  32. PAHO (2000). Pan-american health organisation. manual logistical management of humanitarian supply, www.disaster-info.net, podcast accessed 11 April 2012.

  33. Poojari, C. A., Lucas, C. and Mitra, G. (2008). Robust solutions and risk measures for a supply chain planning problem under uncertainty, Journal of the Operational Research Society 59, 1, pp. 2–12.

    Google Scholar 

  34. Rottkemper, B., Fischer, K., Blecken, A. and Danne, C. (2011). Inventory relocation for overlapping disaster settings in humanitarian operations, OR Spectrum 33, pp. 721–749.

    Google Scholar 

  35. Sphere Project (2004). Humanitarian charter and minimum standards in disaster response, www.sphereproject.org, accessed 11 April 2012.

  36. Thomas, A. (2003). Humanitarian logistics: Enabling disaster response www.fritzinstitute.org, accessed 11 April 2012.

  37. Thomas, A. (2005). Matching recognition with responsibility, www.fritzinstitute.org, accessed 11 April 2012.

  38. Tomasini, R. and Van Wassenhove, L. N. (2004). A framework to unravel, prioritize and coordinate vulnerability and complexity factors affecting a humanitarian operation, knowledge. insead.edu, accessed 11 April 2012.

    Google Scholar 

  39. Tsui, E. (2002). Initial response to complex emergencies and natural disasters, in K. M. Cahill (ed.), Emergency Relief Operations, chap. 2 (Fordham University Press, New York), pp. 32–54.

    Google Scholar 

  40. UNISDR (2005a). United Nations international strategy for disaster reduction, Emergency preparedness for effective response: Strengthening institutional capacities, www.unisdr.org, accessed 11 April 2012.

  41. UNISDR (2005b). United Nations international strategy for disaster reduction, Proceedings of the conference building the resilience of nations and communities to disasters, www.unisdr.org, accessed 11 April 2012.

  42. Van Wassenhove, L. N. (2006). Humanitarian aid logistics: supply chain management in high gear journal of the operational research society, Journal of the Operational Research Society 57, 5, pp. 475–489.

    Google Scholar 

  43. Van Wassenhove, L. N. and Pedraza Martinez, A. J. (2010). Using or to adapt supply chain management best practices to humanitarian logistics, International Transactions in Operational Research.

    Google Scholar 

  44. Vitoriano, B., Ortuño, M., Tirado, G. and Montero, J. (2011). A multi-criteria optimization model for humanitarian aid distribution, Journal of Global Optimization 51, pp. 189–208.

    Google Scholar 

  45. Vitoriano, B., Ortuño, T. and Tirado, G. (2009). HADS, a goal programming-based humanitarian aid distribution system, Journal of MultiCriteria Decision Analysis 16, 2009, pp. 55–64.

    Google Scholar 

  46. Woods, D. F., Barone, A., Murphy, P. and Wardlow, P. (1995). International Logistics (Chapman & Hall, London).

    Google Scholar 

  47. Yi, W. and Ozdamar, L. (2007). A dynamic logistic coordination model for evacuation and support in disaster response activities, European Journal of Operational Research 179, 3, pp. 1177–1193.

    Google Scholar 

Download references

Acknowledgments

We wish to thank the referees for their careful reading of the article. Their constructive comments, queries and suggestions enabled us to improve its quality, clarity and readability.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alistair Clark .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Atlantis Press

About this chapter

Cite this chapter

Clark, A., Culkin, B. (2013). A Network Transshipment Model for Planning Humanitarian Relief Operations After a Natural Disaster. In: Vitoriano, B., Montero, J., Ruan, D. (eds) Decision Aid Models for Disaster Management and Emergencies. Atlantis Computational Intelligence Systems, vol 7. Atlantis Press, Paris. https://doi.org/10.2991/978-94-91216-74-9_11

Download citation

  • DOI: https://doi.org/10.2991/978-94-91216-74-9_11

  • Published:

  • Publisher Name: Atlantis Press, Paris

  • Print ISBN: 978-94-91216-73-2

  • Online ISBN: 978-94-91216-74-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships