Skip to main content
SpringerLink
Log in

Freight Service Provision for Disaster Relief: A Competitive Network Model with Computations

  • Conference paper
  • First Online:
Book cover Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights (DOD 2015 2016)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 185))

Included in the following conference series:

  • 1080 Accesses

Abstract

In this paper, we develop a competitive freight service provision network model for disaster relief. A humanitarian relief organization is interested in determining its most cost-effective deliveries of needed supplies in a crisis setting. Multiple freight service providers are engaged in competition to acquire the business of carrying the supplies in the amounts desired to the destinations. We describe the objective functions faced by the various decision-makers and their underlying constraints, and present the optimality conditions. We then define the freight service provision network equilibrium for disaster relief and formulate it as a variational inequality problem. We provide qualitative results for the equilibrium product shipment pattern in terms of existence and uniqueness. For completeness, we also construct a new cooperative system-optimization model and discuss the price of anarchy relating the two models, along with additional theoretical results. In addition, we propose algorithmic schemes that take advantage of the underlying network structure of the problem. We present a case study on the shipment of personal protective equipment supplies in the context of the Ebola humanitarian healthcare crisis in west Africa. The computational results in this paper yield insights on the equilibrium shipment and price patterns in the freight service provision sector for humanitarian operations in terms of enhanced or reduced competition, as well as increases in demand.

To appear in Dynamics of Disasters, I.S. Kotsireas, A. Nagurney, and P.M. Pardalos, Eds., Springer International Publishing Switzerland.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

References

  • Ap, T.: Ebola crisis: WHO slammed by Harvard-convened over slow response. CNN, 23 Nov 2015

    Google Scholar 

  • Apex: Introducing apex emergency response freight services? The calm during the storm, Lafayette, LA (2015)

    Google Scholar 

  • Balcik, B., Ak, D.: Supplier selection for framework agreements in humanitarian relief. Prod. Oper. Manag. 23 (6), 1028–1041 (2014)

    Article  Google Scholar 

  • Balcik, B., Beamon, B.M., Smilowitz, K.: Last mile distribution in humanitarian relief. J. Intell. Transp. Syst. 12 (2), 51–63 (2008)

    Article  Google Scholar 

  • Barbarosoglu, G., Arda, Y.: A two-stage stochastic programming framework for transportation planning in disaster response. J. Oper. Res. Soc. 55 (1), 43–53 (2004)

    Article  MATH  Google Scholar 

  • Barbarosoglu, G.L., Ozdamar, A., Cevik, A.: An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. Eur. J. Oper. Res. 140 (1), 118–133 (2002)

    Article  MATH  Google Scholar 

  • Bertsekas, D.P., Gafni, E.M.: Projection methods for variational inequalities with application to the traffic assignment problem. In: Nondifferential and Variational Techniques in Optimization. Mathematical Programming Study, vol. 27, pp. 139–159. Springer, Berlin (1982)

    Google Scholar 

  • Centers for Disease Control and Prevention: 2014 Ebola outbreak in west Africa - Case counts. http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/case-counts.html (2016)

  • Dafermos, S.: Traffic equilibrium and variational inequalities. Transp. Sci. 14, 42–54 (1980)

    Article  MathSciNet  Google Scholar 

  • Dafermos, S.C., Sparrow, F.T.: The traffic assignment problem for a general network. J. Res. Natl. Bur. Stand. 73B, 91–118 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  • Falasca, M., Zobel, C.W.: A two-stage procurement model for humanitarian relief supply chains. J. Humanitarian Logist. Supply Chain Manag. 1 (2), 151–169 (2011)

    Article  Google Scholar 

  • Fischer, W.A. II, Hynes, N.A., Perl, T.M.: Protecting healthcare workers from Ebola: personal protective equipment is critical but not enough. Ann. Intern. Med. 161 (10), 753–754 (2014)

    Article  Google Scholar 

  • Gabay, D., Moulin, H.: On the uniqueness and stability of Nash equilibria in noncooperative games. In: Bensoussan, A., Kleindorfer, P., Tapiero, C.S. (eds.) Applied Stochastic Control of Econometrics and Management Science, pp. 271–294. North-Holland, Amsterdam (1980)

    Google Scholar 

  • Hoxtell, W., Norz, M., Teicke, M.: Business engagement in humanitarian response and disaster risk management. Global Public Policy Institute, Berlin, Germany, May 2015

    Google Scholar 

  • Huang, M., Smilowitz, K., Balcik, B.: Models for relief routing: equity, efficiency and efficacy. Transp. Res. E 48, 2–18 (2012)

    Article  Google Scholar 

  • International Federation of Red Cross and Red Crescent Societies: Scope of service. http://www.ifrc.org/en/what-we-do/logistics/procurement/supply-services/ (2016)

  • Kinderlehrer, D., Stampacchia, G.: An Introduction to Variational Inequalities and Their Applications. Academic, New York (1980)

    MATH  Google Scholar 

  • Knobler, S., Mahmoud, A., Lemon, S., Pray, L. (eds.): The Impact of Globalization on Infectious Disease Emergence and Control: Exploring the Consequences and Opportunities. The National Academies Press, Washington, DC (2006)

    Google Scholar 

  • Kumar, S.: Managing risks in a relief supply chain in the wake of an adverse event. Oper. Res. Insight 24 (2), 131–157 (2011)

    Google Scholar 

  • Lodree, E.J., Carter, D., Barbee, E.: The donation collections routing problem. In: Kotsireas, I.S., Nagurney, A., Pardalos, P.M. (eds.) Dynamics of Disasters. Springer International Publishing, Cham (2016)

    Google Scholar 

  • Mete, H.O., Zabinsky, Z.B.: Stochastic optimization of medical supply location and distribution in disaster management. Int. J. Prod. Econ. 126, 76–84 (2010)

    Article  Google Scholar 

  • Miller-Hooks, E., Sorrel, G.: The maximal dynamic expected flows problem for emergency evacuation planning. Transp. Res. Rec. 2089, 26–34 (2008)

    Article  Google Scholar 

  • Na, H.S., Banerjee, A.: A disaster evacuation network model for transporting multiple priority evacuees. IIE Trans. 47 (11), 1287–1299 (2015)

    Article  Google Scholar 

  • Nagurney, A.: Network Economics: A Variational Inequality Approach, second and revised edition. Kluwer Academic, Dordrecht (1999)

    Book  Google Scholar 

  • Nagurney, A.: Supply Chain Network Economics: Dynamics of Prices, Flows, and Profits. Edward Elgar Publishing, Cheltenham (2006)

    Google Scholar 

  • Nagurney, A., Masoumi, A.H.: Supply chain network design of a sustainable blood banking system. In: Boone, T., Jayaraman, V., Ganeshan, R. (eds.) Sustainable Supply Chains: Models, Methods and Public Policy Implications, pp. 49–72. Springer, London (2012)

    Chapter  Google Scholar 

  • Nagurney, A., Nagurney, L.S.: A mean-variance disaster relief supply chain network model for risk reduction with stochastic link costs, time targets, and demand uncertainty. In: Kotsireas, I.S., Nagurney, A., Pardalos, P.M. (eds.) Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights. Springer International Publishing, 231–255 (2016)

    Google Scholar 

  • Nagurney, A., Qiang, Q.: Fragile Networks: Identifying Vulnerabilities and Synergies in an Uncertain World. Wiley, Hoboken, NJ (2009)

    Book  MATH  Google Scholar 

  • Nagurney, A., Qiang, Q.: Fragile networks: identifying vulnerabilities and synergies in an uncertain age. Int. Trans. Oper. Res. 19, 123–160 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  • Nagurney, A., Dong, J., Zhang, D.: A supply chain network equilibrium model. Transp. Res. E 38, 281–303 (2002)

    Article  Google Scholar 

  • Nagurney, A., Yu, M., Qiang, Q.: Multiproduct humanitarian healthcare supply chains: a network modeling and computational framework. In: Proceedings of the 23rd Annual POMS Conference, Chicago, IL (2012)

    Google Scholar 

  • Nagurney, A., Yu, M., Floden, J., Nagurney, L.S.: Supply chain network competition in time-sensitive markets. Transp. Res. E 70, 112–127 (2014)

    Article  Google Scholar 

  • Nagurney, A., Masoumi, A.H., Yu, M.: An integrated disaster relief supply chain network model with time targets and demand uncertainty. In: Nijkamp, P., Rose, A., Kourtit, K. (eds.) Regional Science Matters: Studies Dedicated to Walter Isard, pp. 287–318. Springer International Publishing, Cham (2015a)

    Google Scholar 

  • Nagurney, A., Saberi, S., Shivani, S., Floden, J.: Supply chain network competition in price and quality with multiple manufacturers and freight service providers. Transp. Res. E 77, 248–267 (2015b)

    Google Scholar 

  • Patriksson, M.: The Traffic Assignment Problem. VSP, Utrecht (1994)

    MATH  Google Scholar 

  • Pedraza Martinez, A.J., Stapleton, O., Van Wassenhove, L.N.: Field vehicle fleet management in humanitarian operations: a case-based approach. J. Oper. Manag. 29 (5), 404–421 (2011)

    Article  Google Scholar 

  • Qiang, Q., Nagurney, A.: A bi-criteria indicator to assess supply chain network performance for critical needs under capacity and demand disruptions. Transp. Res. A 46 (5), 801–812 (2012)

    Google Scholar 

  • Regnier, E.: Public evacuation decisions and hurricane track uncertainty. Manag. Sci. 54 (2), 16–28 (2008)

    Article  Google Scholar 

  • Rottkemper, B., Fischer, K., Blecken, A.: A transshipment model for distribution and inventory relocation under uncertainty in humanitarian operations. Socio Econ. Plan. Sci. 46, 98–109 (2012)

    Article  Google Scholar 

  • Roughgarden, T.: Selfish Routing and the Price of Anarchy. MIT Press, Cambridge, MA (2005)

    MATH  Google Scholar 

  • Saadatseresht, M., Mansourian, A., Taleal, M.: Evacuation planning using multiobjective evolutionary optimization approach. Eur. J. Oper. Res. 198, 305–314 (2009)

    Article  MATH  Google Scholar 

  • Sheffi, Y., Mahmassani, H., Powell, W.B.: A transportation network evacuation model. Transp. Res. A 16 (3), 209–218 (1982)

    Article  Google Scholar 

  • Sherali, H.D., Carter, T.B., Hobeika, A.G.: A transportation network evacuation model. Transp. Res. A 16 (3), 209–218 (1991)

    Google Scholar 

  • Sheu, J.B.: An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transp. Res. E 43 (6), 687–709 (2007)

    Article  MathSciNet  Google Scholar 

  • The World Bank: Cost to export (US$ per container). http://data.worldbank.org/indicator/IC.EXP.COST.CD (2016)

  • Tzeng, G.-H., Cheng, H.-J., Huang, T.: Multi-objective optimal planning for designing relief delivery systems. Transp. Res. E 43 (6), 673–686 (2007)

    Article  Google Scholar 

  • United Nations High Commissioner for Refugees: Doing business with UNHCR. UNHCR Global Service Centre, Budapest (2015)

    Google Scholar 

  • United States Department of Commerce: Access costs everywhere. http://acetool.commerce.gov/shipping (2016)

  • UNOPS: Procurement manual, revision 5, May 1. Sustainable Practice Procurement Group (2014)

    Google Scholar 

  • Van Wassenhove, L.N.: Blackett memorial lecture. Humanitarian aid logistics: supply chain management in high gear. J. Oper. Res. Soc. 57 (5), 475–489 (2006)

    Google Scholar 

  • Vitoriano, B., Ortuño, M., Tirado, G., Montero, M.: A multi-criteria optimization model for humanitarian aid distribution. J. Glob. Optim. 51, 189–208 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  • Vogiatzis, C., Pardalos. P.M.: Evacuation modeling and betweenness centrality. In: Kotsireas, I.S., Nagurney, A., Pardalos, P.M. (eds.) Dynamics of Disasters. Springer International Publishing, Cham (2016)

    Google Scholar 

  • Vogiatzis, C., Walteros, J.L., Pardalos, P.M.: Evacuation through clustering techniques. In: Goldengorin, B., Kalyagin, V.A., Pardalos, P.M. (eds.) Models, Algorithms, and Technologies for Network Analysis, pp. 185–198. Springer, New York (2013)

    Chapter  Google Scholar 

  • Wilson, D.: CE: inside an Ebola ET: a nurses’ report. Am. J. Nurs. 115 (12), 28–38 (2015)

    Article  Google Scholar 

  • Woods, R.: DHL, Qatar overcome logistics challenges in Nepal. Air Cargo World, 1 June 2015

    Google Scholar 

  • World Health Organization: Health worker Ebola infections in Guinea, Liberia and Sierra Leone: a preliminary report, Geneva, 21 May 2015

    Google Scholar 

  • Yi, W., Kumar, A.: Ant colony optimization for disaster relief operations. Transp. Res. E 43 (6), 660–672 (2007)

    Article  Google Scholar 

Download references

Acknowledgements

The author acknowledges the constructive comments and suggestions of the anonymous reviewer on an earlier version of this paper

The author thanks Professor Panos M. Pardalos of the University of Florida and Professor Ilias Kootsireas of Wilfrid Laurier University for the wonderful collaboration on the co-organization of the 2nd International Conference on Dynamics of Disasters, which took place in Kalamata, Greece, June 29–July 2, 2015.

Author information

Authors and Affiliations

  1. Department of Operations and Information Management, Isenberg School of Management, University of Massachusetts, Amherst, MA, 01003, USA

    Anna Nagurney

Authors
  1. Anna Nagurney
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anna Nagurney .

Editor information

Editors and Affiliations

  1. Department of Physics and Computer Science, Wilfrid Laurier University, Waterloo, Ontario, Canada

    Ilias S. Kotsireas

  2. Department of Operations and Information Management, University of Massachusetts, Amherst, Massachusetts, USA

    Anna Nagurney

  3. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Nagurney, A. (2016). Freight Service Provision for Disaster Relief: A Competitive Network Model with Computations. In: Kotsireas, I., Nagurney, A., Pardalos, P. (eds) Dynamics of Disasters—Key Concepts, Models, Algorithms, and Insights. DOD 2015 2016. Springer Proceedings in Mathematics & Statistics, vol 185. Springer, Cham. https://doi.org/10.1007/978-3-319-43709-5_11

Download citation

Publish with us

Policies and ethics

Search

Navigation