Skip to main content
Intended for healthcare professionals
Restricted access
Research article
First published online January 1, 2012

Case Study–Based Evaluation of Stochastic Multicommodity Emergency Inventory Management Model

Abstract

Emergency disaster management has emerged as a vital tool for reducing the harm and alleviating the suffering that disasters worldwide cause their victims. A significant task of planners involved in emergency disaster management is the ability to plan for and satisfy the vital needs of the people located in emergency shelters, such as the Superdome in New Orleans, Louisiana, which was used as a shelter during Hurricane Katrina. This task requires determination of a way to reduce the uncertainties associated with emergency operations and to estimate the expected costs of delivery and consumption of vital supplies throughout these operations. This paper attempts to address these issues by application of a case study–based approach to demonstrate the usefulness of a stochastic humanitarian inventory control model and estimation of the minimum safety stock levels of emergency inventories. The emergency inventory management problem is discussed, and previous emergency inventory studies are reviewed to identify the need for a stochastic emergency inventory management model. After introduction of the mathematical formulation for the model, the formulation is applied to a number of realistic case studies built on the basis of the experiences in recent major disasters, such as Hurricane Katrina. The paper concludes with a summary of lessons learned for the model when it is applied to a wide range of scenarios drawn from real-life experiences and used to create emergency inventory management strategies for different types of disasters.

Get full access to this article

View all access and purchase options for this article.

References

1. National Research Council. Improving Disaster Management: The Role of IT in Mitigation, Preparedness, Response, and Recovery. The National Academies Press, Washington, D.C., 2007.
2. Noji E. K. The Nature of Disaster: General Characteristics and Public Health Effects. In The Public Health Consequences of Disasters (Noji E. K., ed.), Oxford University Press, Oxford, United Kingdom, 1997, pp. 3–20.
3. Holguin-Veras J., Perez N., Ukkusuri S.V., Wachtendorf T., and Brown B. Emergency Logistics Issues Affecting the Response to Katrina: A Synthesis and Preliminary Suggestions for Improvement. In Transportation Research Record: Journal of the Transportation Research Board, No. 2022, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 76–82.
4. EM-DAT. The International Disaster Database. Centre for Research on the Epidemiology of Disasters, Brussels, Belgium. http://www.emdat.be.
5. Van Wyk E. Strategic Inventory Management for Disaster Relief. BS thesis. University of Pretoria, Pretoria, South Africa, 2010.
6. Taskin S., and Lodree E. J. Jr., Inventory Decisions for Emergency Supplies Based on Hurricane Count Predictions. International Journal of Production Economics, Vol. 126, 2010, pp. 66–75.
7. Rawls C.G., and Turnquist M. A. Pre-Positioning of Emergency Supplies for Disaster Response. Transportation Research Part B, Vol. 44, 2010, pp. 521–534.
8. Lodree E.J. Jr., Pre-Storm Emergency Supplies Inventory Planning. Journal of Humanitarian Logistics and Supply Chain Management, Vol. 1, No. 1, 2011, pp. 50–77.
9. Yushimito W.F., Jaller M.A., and Ukkusuri S. V. Facility Location in Disasters: Voronoi-Based Heuristic Algorithm with Application to Hurricane Katrina. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.
10. Jia H., Ordonez F., and Dessouky M. A Modeling Framework for Facility Location of Medical Services for Large-Scale Emergencies. IIE Transactions, Vol. 39, 2007, pp. 41–55.
11. Duran S., Gutierrez M.A., and Keskinocak P. Pre-Positioning of Emergency Items Worldwide for CARE International. Interfaces, Vol. 41, No. 3, 2011, pp. 223–237.
12. Balcik B., and Beamon B. M. Facility Location in Humanitarian Relief. International Journal of Logistics: Research and Applications, Vol. 11, No. 2, 2008, pp. 101–121.
13. Haghani A., and Oh S. Formulation and Solution of a Multi-Commodity, Multi-Modal Network Flow Model for Disaster Relief Operations. Transportation Research Part A, Vol. 30, 1996, pp. 231–250.
14. Barbarosoglu G., and Arda Y. A Two-Stage Stochastic Programming Framework for Transportation Planning in Disaster Response. Journal of the Operational Research Society, Vol. 55, 2004, pp. 43–53.
15. Lin Y. -H., Batta R., Rogerson P., Blatt A., and Flanigan M. Application of a Humanitarian Relief Logistics Model to an Earthquake Disaster. Presented at 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010.
16. Friedrich F., Gehbauer F., and Rickers U. Optimized Resource Allocation for Emergency Response After Earthquake Disasters. Safety Science, Vol. 35, 2000, pp. 41–57.
17. Yang N., and Federgruen A. Safeguarding Strategic Supplies: Selecting an Optimal Set of Suppliers. DOTM Colloquium Series. Anderson School of Management, University of California, Los Angeles, 2006.
18. Chang M. -S., Tseng Y. -L., and Chen J.-W. A Scenario Planning Approach for the Flood Emergency Logistics Preparation Problem Under Uncertainty. Transportation Research Part E, Vol. 43, 2007, pp. 737–754.
19. Tzeng G. -H., Cheng H. -J., and Huang T. D. Multi-Objective Optimal Planning for Designing Relief Delivery Systems. Transportation Research Part E, Vol. 43, 2007, pp. 673–686.
20. Ozdamar L., Ekinci E., and Kucukyazici B. Emergency Logistics Planning in Natural Disasters. Annals of Operations Research, Vol. 129, 2004, pp. 217–245.
21. Ozdamar L., and Yi W. Greedy Neighborhood Search for Disaster Relief and Evacuation Logistics. IEEE Intelligent Systems, Vol. 23, No. 1, 2008, pp. 14–23.
22. Yi W., and Kumar A. Ant Colony Optimization for Disaster Relief Operations. Transportation Research Part E, Vol. 43, 2007, pp. 660–672.
23. Barbarosoglu G., Ozdamar L., and Cevik A. An Interactive Approach for Hierarchical Analysis of Helicopter Logistics in Disaster Relief Operations. European Journal of Operational Research, Vol. 140, 2002, pp. 118–133.
24. Beamon B.M., and Kotleba S. A. Inventory Modelling for Complex Emergencies in Humanitarian Relief Operations. International Journal of Logistics: Research and Applications, Vol. 9, No. 1, 2006, pp. 1–18.
25. Ozbay K., and Ozguven E. E. Stochastic Humanitarian Inventory Control Model for Disaster Planning. In Transportation Research Record: Journal of the Transportation Research Board, No. 2022, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 63–75.
26. Ozguven E.E., and Ozbay K. A Secure and Efficient Inventory Management System for Disasters. Transportation Research Part C. 2011.
27. Jaller M., Ukkusuri S., and Holguin-Veras J. A Stochastic Inventory Model for Fixed Lifetime Goods for Disaster Planning. Presented at INFORMS Annual Meeting, Seattle, Wash., 2007.
28. Dessouky M., Ordonez F., Jia H., and Shen Z. Rapid Distribution of Medical Supplies. International Series in Operations Research and Management Science, Vol. 91, 2006, 309–338.
29. Yi W., and Ozdamar L. A Dynamic Logistics Coordination Model for Evacuation and Support in Disaster Response Activities. European Journal of Operational Research, Vol. 179, No. 3, 2007, pp. 1177–1193.
30. Kongsomsaksakul S., Yang C., and Chen A. Shelter Location–Allocation Model for Flood Evacuation Planning. Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, 2005, pp. 4237–4252.
31. Han Y., Guan X., and Shi L. Optimal Supply Location Selection and Routing for Emergency. Proc., IEEE Conference on Automation Science and Engineering, Scottsdale, Ariz, 2007, pp. 1039–1044.
32. Sherali H.D., Carter T.B., and Hobeika A. G. A Location/Allocation Model and Algorithm for Evacuation Planning Under Hurricane/Flood Conditions. Transportation Research Part B, Vol. 25, No. 6, 1991, pp. 439–452.
33. Mete H.O., and Zabinsky Z. B. Stochastic Optimization of Medical Supply Location and Distribution in Disaster Management. International Journal of Production Economics, Vol. 126, 2010, pp. 76–84.
34. Prékopa A. On the Hungarian Inventory Control Model. European Journal of Operational Research, Vol. 171, 2006, pp. 894–914.
35. Noyan N., and Prékopa A. A Variant of the Hungarian Inventory Control Model. International Journal of Production Economics, Vol. 103, No. 2, 2006, pp. 784–797.
36. Prékopa A. Multivariate Value at Risk and Other Topics. Annals of Operations Research, Vol. 193, No. 1, 2012, pp. 49–69.
38. Lee Y.M., Ghosh S., and Ettl M. Simulating Distribution of Emergency Relief Supplies for Disaster Response Operations. Proc., Winter Simulation Conference, Austin, Tex., 2009, pp. 2797–2808.
39. Azzalini A., and Vella A. Dalla. The Multivariate Skew-Normal Distribution. Biometrika, Vol. 83, No. 4, 1996, pp. 715–726.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: January 1, 2012
Issue published: January 2012

Rights and permissions

© 2012 National Academy of Sciences.
Request permissions for this article.

Authors

Affiliations

Eren Erman Ozguven
Department of Civil and Environmental Engineering, Rutgers University, 623 Bowser Road, Piscataway, NJ 08854.
Kaan Ozbay
Department of Civil and Environmental Engineering, Rutgers University, 623 Bowser Road, Piscataway, NJ 08854.

Notes

Metrics and citations

Metrics

Journals metrics

This article was published in Transportation Research Record: Journal of the Transportation Research Board.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 65

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 0

Crossref: 11

  1. Critical Decision-Making Issues in Disaster Relief Supply Management: ...
    Go to citation Crossref Google Scholar
  2. Emergency logistics network design based on space–time resource config...
    Go to citation Crossref Google Scholar
  3. A systematic literature review about dimensioning safety stock under u...
    Go to citation Crossref Google Scholar
  4. Operations research models and methods for safety stock determination:...
    Go to citation Crossref Google Scholar
  5. A two-stage approach to agile pharmaceutical supply chain management w...
    Go to citation Crossref Google Scholar
  6. Statistical model checking of relief supply location and distribution ...
    Go to citation Crossref Google Scholar
  7. A hybrid inventory policy with split delivery under regular and surge ...
    Go to citation Crossref Google Scholar
  8. Towards an Agent-Based Humanitarian Relief Inventory Management System
    Go to citation Crossref Google Scholar
  9. An RFID-based inventory management framework for emergency relief oper...
    Go to citation Crossref Google Scholar
  10. A hybrid inventory management system responding to regular demand and ...
    Go to citation Crossref Google Scholar
  11. An RFID-based inventory management framework for efficient emergency r...
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.

View options

PDF/ePub

View PDF/ePub