Skip to main content
Intended for healthcare professionals
Restricted access
Research article
First published online January 1, 2014

Dual-Route Distribution Strategy with Supply Chain Disruption

Abstract

Unexpected disruptions in the supply chain can directly and indirectly cause additional logistics costs because of delayed delivery. Previous studies have minimized the additional cost with a network design that used the concept of level of service and unit delay cost; however, in cases of disruption in a regional distribution center (RDC), companies commonly must secure a bypass through another RDC and pay more to use a faster transportation mode. The aim of this study is to develop a dual-route distribution strategy to minimize the logistics costs that stem from the disruption in the RDC. The model addressed in this study determines the RDC allocation and the freight dualization ratio to establish a bypass before a disruption occurs and to ensure the punctuality of delivery without losses due to late delivery. An application of the model uses an actual company's network data. The results of this application show that the dual-route distribution strategy can be more advantageous than a single-route distribution strategy. The model provides a theoretical basis for the use of the dual-route strategy to minimize the direct and indirect costs associated with the RDC disruption.

Get full access to this article

View all access and purchase options for this article.

References

1. Zhang Z., and Figliozzi M. A. A Survey of China's Logistics Industry and the Impacts of Transport Delays on Importers and Exporters. Transport Reviews, Vol. 30, No. 2, 2009, pp. 179–194.
2. Snyder L. V., Bulut Z., Peng P., Rong Y., Schmitt A. J., and Sinsoysal B. Supply Chain Disruptions: A Review. Working Paper. Lehigh University, Bethlehem, Pa., 2010.
3. Mitchell V. W. Organizational Risk Perception and Reduction: A Literature Review. British Journal of Management, Vol. 6, No. 2, 1995, pp. 115–133.
4. Chopra S., and Sodhi M. M. S. Supply-Chain Breakdown. MIT Sloan Management Review, 2004.
5. Rice J. B., and Caniato F. Building a Secure and Resilient Supply Network. Supply Chain Management Review, Vol. 7, No. 5, 2003, pp. 22–30.
6. Steele P. T., and Court B. H. Profitable Purchasing Strategies: A Manager's Guide for Improving Organizational Competitiveness Through the Skills of Purchasing. McGraw-Hill School Education Group, New York, 1996.
7. La Londe B. J. Supply Chain Management: Myth or Reality? Supply Chain Management Review, Vol. 1, No. 1, 1997, pp. 6–7.
8. Jüttner U., Peck H., and Christopher M. Supply Chain Risk Management: Outlining an Agenda for Future Research. International Journal of Logistics Research and Applications, Vol. 6, No. 4, 2003, pp. 197–210.
9. Deloitte Survey: Executives Face Growing Threats to Their Supply Chains. Business Credit, Vol. 115, No. 6, 2013.
10. Smeltzer L. R., and Siferd S. P. Proactive Supply Management: The Management of Risk. Journal of Supply Chain Management, Vol. 34, No. 1, 1998, pp. 38–45.
11. Mentzer J. T. Fundamentals of Supply Chain Management: Twelve Drivers of Competitive Advantage. Sage Publications, Thousand Oaks, Calif., 2004.
12. Dan W., and Zan Y. Risk Management of Global Supply Chain. Proc., International Conference on Automation and Logistics, IEEE, New York, 2007, pp. 1150–1155.
13. Sheffi Y., Rice J. B., Fleck J. M., and Caniato F. Supply Chain Response to Global Terrorism: A Situation Scan. Proc., EurOMA–POMS Joint International Conference, Lake Como, Italy, European Operations Management Association, Brussels, Belgium, 2003.
14. Snyder L. V. Facility Location under Uncertainty: A Review. IIE Transactions, Vol. 38, No. 7, 2006, pp. 547–564.
15. Snyder L. V., Daskin M. S., and Teo C. P. The Stochastic Location Model with Risk Pooling. European Journal of Operational Research, Vol. 179, No. 3, 2007, pp. 1221–1238.
16. Eppen G. D. Effects of Centralization on Expected Costs in a Multi-Location Newsboy Problem. Management Science, Vol. 25, No. 5, 1979, pp. 498–501.
17. Schwarz L. B. Multi-level Production/Inventory Control Systems: Theory and Practice. North-Holland Publishing Company, Amsterdam, Netherlands, 1981.
18. Meller R. D. The Impact of Multiple Stocking Points on System Profitability. International Journal of Production Economics, Vol. 38, Nos. 2-3, 1995, pp. 209–214.
19. Shen Z.-J.M., Coullard C., and Daskin M. S. A Joint Location-Inventory Model. Transportation Science, Vol. 37, No. 1, 2003, pp. 40–55.
20. Daskin M. S., Coullard C. R., and Shen Z.-J. M. An Inventory-Location Model: Formulation, Solution Algorithm and Computational Results. Annals of Operations Research, Vol. 110, No. 1, 2002, pp. 83–106.
21. Jeon H. M., and Lawrence V. S. A Capacitated Location-Inventory Model with Unreliable Supplies. Proc., Autumn Conference, Korean Institute of Industrial Engineers, Seoul, South Korea, 2008, pp. 261–267.
22. Chen Q., Li X., and Ouyang Y. Joint Inventory-Location Problem under the Risk of Probabilistic Facility Disruptions. Transportation Research Part B: Methodological, Vol. 45, No. 7, 2011, pp. 991–1003.
23. Weaver J. R., and Church R. L. A Median Location Model with Nonclosest Facility Service. Transportation Science, Vol. 19, No. 1, 1985, pp. 58–74.
24. Snyder L. V., and Daskin M. S. Reliability Models for Facility Location: The Expected Failure Cost Case. Transportation Science, Vol. 39, No. 3, 2005, pp. 400–416.
25. Pirkul H., Narasimhan S., and De P. Locating Concentrators for Primary and Secondary Coverage in a Computer Communications Network. IEEE Transactions on Communications, Vol. 36, No. 4, 1988, pp. 450–458.
26. Li X. An Integrated Modeling Framework for Design of Logistics Networks with Expedited Shipment Services. Transportation Research Part E: Logistics and Transportation Review, Vol. 56, 2013, pp. 46–63.
27. Starr M. K., and Miller D. W. Inventory Control: Theory and Practice. Prentice Hall, Englewood Cliffs, N.J., 1962.
28. Cornuejols G., Nemhauser G. L., and Wolsey L. A. The Uncapacitated Facility Location Problem. Defense Technical Information Center Document. Carnegie-Mellon University, Pittsburgh, Pa., 1983.
29. Pirkul H. The Uncapacitated Facility Location Problem with Primary and Secondary Facility Requirements. IIE Transactions, Vol. 21, No. 4, 1989, pp. 337–348.
30. Yapicioglu H., Smith A. E., and Dozier G. Solving the Semi-desirable Facility Location Problem Using Bi-objective Particle Swarm. European Journal of Operational Research, Vol. 177, No. 2, 2007, pp. 733–749.
31. Bozorgi-Amiri A., Jabalameli M., Alinaghian M., and Heydari M. A Modified Particle Swarm Optimization for Disaster Relief Logistics under Uncertain Environment. International Journal of Advanced Manufacturing Technology, Vol. 60, No. 1, 2012, pp. 357–371.
32. Guner A. R., and Sevkli M. A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem. Journal of Artificial Evolution and Applications, Vol. 2008, 2008, pp. 1–9.
33. Elbeltagi E., Hegazy T., and Grierson D. Comparison among Five Evolutionary-based Optimization Algorithms. Advanced Engineering Informatics, Vol. 19, No. 1, 2005, pp. 43–53.
34. Sevkli M., and Guner A. A Continuous Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem: Ant Colony Optimization and Swarm Intelligence. Lecture Notes in Computer Science, No. 4150, 2006, pp. 316–323.
35. Birge B. PSOt: A Particle Swarm Optimization Toolbox for Use with MATLAB. Proc., Swarm Intelligence Symposium, SIS ‘03, Saint Louis, Mo., IEEE, New York, 2003, pp. 182–186.

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, 2014
Issue published: January 2014

Rights and permissions

© 2014 National Academy of Sciences.
Request permissions for this article.

Authors

Affiliations

Sung Ho Hur
Department of Logistics Research, Division for Logistics Technology and Market Analysis, Korea Transport Institute, 315 Goyangdaero, Ilsanseo-Gu, Goyang City, Gyeonggi-Do 411–701, South Korea.
Dong-Kyu Kim
Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, South Korea, 151–744.
Seung-Young Kho
Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, South Korea, 151–744.
Chungwon Lee
Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, South Korea, 151–744.

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: 60

*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: 0

There are no citing articles to show.

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