Military Logistics Planning in Humanitarian Relief Operations

  • Samir Sebbah
  • Abdeslem Boukhtouta
  • Jean Berger
  • Ahmed Ghanmi
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 54)


Humanitarian logistics is defined as the process of planning, implementing and controlling the efficient, cost effective flow and storage of goods and materials as well as related information from the point of origin to the point of consumption for the purpose of alleviating the suffering of vulnerable people. The function encompasses a range of activities, including preparedness, planning, procurement, transport, warehousing, tracking and tracing. However, several factors may obstruct the flows of reliefs and information in humanitarian relief operations and negatively affect the effectiveness of the involved organizations. Problems such as scarcity of reliefs and logistics means to efficiently distribute the goods, location/allocation of distribution centres and storage capacity, flow bottlenecks in the humanitarian relief network, security of convoys, fairness in reliefs’ distribution, etc. may appear at different stages of the HROs and prevent the reliefs from reaching the needy populations. This chapter considers HROs from a military logistics perspective. We review some challenging problems in HROs. We then propose mathematical planning and optimization models to address some of these problems. Finally, we give some concluding remarks and some future research venues.


Time Slot Column Generation Vehicle Route Problem Military Force Humanitarian Organization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Altay N, Green WG III. Or/ms research in disaster operations management. Eur J Oper Res. 2006;175(1):475–93.CrossRefGoogle Scholar
  2. Balcik B, Beamon B, Smilowitz K. Last mile distribution in humanitarian relief. J Intelli Transp Syst. 2008;12(2):51–63.CrossRefGoogle Scholar
  3. Barbarosoglu G, Ozdamar L, Cevik A. An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. Eur J Oper Res. 2002;140(1):118–33.CrossRefGoogle Scholar
  4. Beresford AKC, Rugamba A. Evaluation of the transport sector in Rwanda. Geneva: UNCTAD; 1996.Google Scholar
  5. Campbell AM, Vandenbussche D, Hermann W. Routing for relief efforts. Transp Sci. 2008;42(2):127–45.CrossRefGoogle Scholar
  6. Chang MS, Tseng YL, Chen JW. A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transp Res Part E: Logist Transp Rev. 2007;43(6):737–54.CrossRefGoogle Scholar
  7. Chief of Force Development. Integrated Capstone Concept. National Defence of Canada; 2009a.Google Scholar
  8. Chief of Force Development. The Future Security Environment 2008–2030. Part 1: current and emerging Trends. National Defence of Canada; 2009b.Google Scholar
  9. Cruijssen F, Cools M, Dullaert W. Horizontal cooperation in logistics: opportunities and impediments. Transp Res Part E: Logist Transp Rev. 2007;43(2):129–42.CrossRefGoogle Scholar
  10. Desrochers M, Desrosiers J, Solomon M. A new optimization algorithm for the vehicle routing problem with time windows. Oper Res. 1992;40(2):342–54. JSTOR, 0030-364X.CrossRefGoogle Scholar
  11. Dickson PD, Mason DW. Analysis of risks associated with reliance on non-integral strategic airlift solutions. Tech rep. 2007;17. DRDC CORAGoogle Scholar
  12. Fisher M. Vehicle routing. Oper Res Manag Sci. 1995;8:1–33.Google Scholar
  13. Ghanmi A, Martel A, Berger J, Boukhtouta A. A methodology for the design and management of Canadian operational supply network. In Proceedings of IEEE Symposium on Computational Intelligence for Security and Defense Applications; 2009. p. 1340–48.Google Scholar
  14. Haghani A, Oh SC. Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transp Res Part A: Policy Practice. 1996;30(3):231–50.CrossRefGoogle Scholar
  15. Huang M, Smilowitz K, Balcik B. Models for relief routing: equity, efficiency and efficacy. Transp Res Part E: Logist Transp Rev. 2011.Google Scholar
  16. Iori M, González JJS, Vigo D. An exact approach for the vehicle routing problem with two-dimensional loading constraints. Transp Sci. 2007;41(2):253–64.CrossRefGoogle Scholar
  17. Jimenez F, Verdegay JL. Solving fuzzy solid transportation problems by an evolutionary algorithm based parametric approach. Eur J Oper Res. 1999;117(3):485–510.CrossRefGoogle Scholar
  18. Kaluzny BL, Erkelens AJ. The optimal MSVS fleet for first-line replenishment. Material group operational research; 2008. DRDC CORA, TR 2006-026.Google Scholar
  19. Knott R. The logistics of bulk relief supplies. Disasters. 1987;11(2):113–5.CrossRefGoogle Scholar
  20. Kovács G, Spens K. Identifying challenges in humanitarian logistics. Int J Phys Distrib Logist Manag. 2009;39(6):506–28.CrossRefGoogle Scholar
  21. Laporte G. The vehicle routing problem: an overview of exact and approximate algorithms. Eur J Oper Res. 1992;59(3):345–58.CrossRefGoogle Scholar
  22. Mete HO, Zabinsky ZB. Stochastic optimization of medical supply location and distribution in disaster management. Int J Prod Eco. 2010;126(1):76–84.CrossRefGoogle Scholar
  23. Nolz P, Doerner K, Gutjahr W, Hartl R. A bi-objective metaheuristic for disaster relief operation planning. Advances in multi-objective nature inspired computing. 2010. p. 167–87.Google Scholar
  24. Oloruntoba R. A wave of destruction and the waves of relief: issues, challenges and strategies. Disaster Prev Manage. 2005;14(4):506–21.CrossRefGoogle Scholar
  25. Özdamar L, Ekinci E, Küçükyazici B. Emergency logistics planning in natural disasters. Ann Oper Res. 2004;29(1):217–45.CrossRefGoogle Scholar
  26. Pettit SJ, Beresford AKC. Emergency relief logistics: an evaluation of military, non-military and composite response models. Int J Logist Res Appl. 2005;8(4):313–31.CrossRefGoogle Scholar
  27. Rawls CG, Turnquist MA. Pre-positioning of emergency supplies for disaster response. Transp Res Part B: Methodol. 2010;44(4):521–34.CrossRefGoogle Scholar
  28. Ribeiro C, Soumis F. A column generation approach to the multi-depot vehicle scheduling problem. Oper Res. 1994;42:41–52.CrossRefGoogle Scholar
  29. Salmerón J, Apte A. Stochastic optimization for natural disaster asset prepositioning. Prod Oper Manage. 2010.Google Scholar
  30. Sebbah S, Ghanmi A, Boukhtouta A. Modeling and simulation of military tactical logistics distribution. In Winter Simulation Conference. 2011. p. 1–11.Google Scholar
  31. Shen Z, Dessouky MM, Ordóez F. A two-stage vehicle routing model for large-scale bioterrorism emergencies. Networks. 2009;54(4):255–69.CrossRefGoogle Scholar
  32. Simpson CN, Hancock PG. Fifty years of operational research and emergency response. J Oper Res Soc. 2009;60(Suppl 1):S126–S139.CrossRefGoogle Scholar
  33. Thomas A. Leveraging private expertise for humanitarian supply chains. Forced Migrat Rev. 2004;21:64–65.Google Scholar
  34. Thomas A. Humanitarian logistics: enabling disaster response. Fritz Inst. 2008.Google Scholar
  35. Thomas A, Kopczak LR. Life-saving supply chains. Building supply chain excellence in emerging economies. 2007. p. 93–111.Google Scholar
  36. Thomas AS, Kopczak LR. From logistics to supply chain management: the path forward in the humanitarian sector. Fritz Inst. 15; 2005.Google Scholar
  37. Tomasini RM, Van Wassenhove LN. From preparedness to partnerships: case study research on humanitarian logistics. International transactions in operations. Research. 2009;16(5):549–59.Google Scholar
  38. Toth P, Vigo D. The vehicle routing problem. Society for Industrial Mathematics. 2002.Google Scholar
  39. Tovia F. An emergency logistics response system for natural disasters. Int J Logist Res Appl. 2007;10(3):173–86.CrossRefGoogle Scholar
  40. Tzeng GH, Cheng HJ, Huang TD. Multi-objective optimal planning for designing relief delivery systems. Transp Res Part E: Logist Transp Rev. 2007;43(6):673–86.CrossRefGoogle Scholar
  41. Van Hentenryck P, Bent R, Coffrin C. Strategic planning for disaster recovery with stochastic last mile distribution. Integration of AI and OR techniques in constraint programming for combinatorial optimization problems. 2010. p. 318–33.Google Scholar
  42. Van Wassenhove LN. Humanitarian aid logistics: supply chain management in high gear. J Oper Res Soc. 2005;57(5):475–89.CrossRefGoogle Scholar
  43. Yi W, Ozdamar L. A dynamic logistics coordination model for evacuation and support in disaster response activities. Eur J Oper Res. 2007;179(3):1177–93.CrossRefGoogle Scholar
  44. Ziliaskopoulos A, Wardell W. An intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays. Eur J Oper Res. 2000;125(3):486–502.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Samir Sebbah
    • 1
  • Abdeslem Boukhtouta
    • 1
  • Jean Berger
    • 2
  • Ahmed Ghanmi
    • 1
  1. 1.Department of National DefenceDefence R&D Canada, Centre for Operational Research & Analysis (DRDC-CORA)OttawaCanada
  2. 2.Department of National DefenceDefence R&D Canada, Valcartier (DRDC-Valcartier)QuebecCanada

Personalised recommendations