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A Multi-Criteria Vertical Coordination Framework for a Reliable Aid Distribution

Journal Name:

  • Journal of Industrial Engineering and Management

Publication Year:

  • 2017
DOI: 
doi.org/10.3926/jiem.2253

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Purpose: This study proposes a methodology that translates multiple humanitarian supply chain stakeholders’ preferences from qualitative to quantitative values, enabling these preferences to be integrated into optimization models to ensure their balanced and simultaneous implementation during the decision-making process. Design/methodology/approach: An extensive literature review is used to justify the importance of developing a strategy that minimizes the impact of a lack of coordination on humanitarian logistics decisions. A methodology for a multi-criteria framework is presented that allows humanitarian stakeholders’ interests to be integrated into the humanitarian decisionmaking process. Findings: The findings suggest that integrating stakeholders’ interests into the humanitarian decision-making process will improve its reliability.Research limitations/implications: To further validate the weights of each stakeholder’s interests obtained from the literature review requires interviews with the corresponding organizations. However, the literature review supports the statements in this paper. Practical implications: The cost of a lack of coordination between stakeholders in humanitarian logistics has been increasing during the last decade. These coordination costs can be minimized if humanitarian logistics’ decision-makers measure and simultaneously consider multiple stakeholders’ preferences. Social implications: When stakeholders’ goals are aligned, the humanitarian logistics response becomes more efficient, increasing the quality of delivered aid and providing timely assistance to the affected population in order to minimize their suffering. Originality/value: This study provides a methodology that translates humanitarian supply chain stakeholders’ interests into quantitative values, enabling them to be integrated into mathematical models to ensure relief distribution based on the stakeholders’ preferences.
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REFERENCES

References: 

Abounacer, R., Renaud, J., & Rekik, M. (2012). An Exact Solution Approach for Multi-Objective
Location-Transportation Problem for Disaster Response. Computers & Operations Research, 41, 83-93.
https://doi.org/10.1016/j.cor.2013.08.001
Adivar, B., & Mert, A. (2010). International disaster relief planning with fuzzy credibility. Fuzzy
Optimization and Decision Making, 9(4), 413-433. https://doi.org/10.1007/s10700-010-9088-8
Afshar, A., & Haghani, A. (2009). Supply chain management in disaster response. Mid-Atlantic Universities
Transportation Center. [online] University of Maryland: Department of Civil & Environmental
Engineering. http://www.mautc.psu.edu/docs/UMD-2008-01.pdf
Akhtar, P., Marr, N.E., & Garnevsca, E.V. (2012). Coordination in humanitarian relief chains: chain
coordinators. Journal of Humanitarian Logistics and Supply Chain Management, 2(1), 85-103.
https://doi.org/10.1108/20426741211226019
Altay, N., & Green, W.G. (2006). OR/MS research in disaster operations management. European Journal of
Operational Research, 175(1), 475-493. https://doi.org/10.1016/j.ejor.2005.05.016
Anaya-Arenas, A.M., Ruiz, A., & Renaud, J. (2013). Models for a fair relief distribution: A network design
problem. Industrial Engineering and Systems Management (IESM). Proceedings of 2013 International
Conference on. 1-8.
Ang, L., & Hern, G. (2015). Retos de la logística humanitaria postdesastre en México ante el cambio climátic. 433.
Balcik, B., & Beamon, B.M. (2008). Facility location in humanitarian relief. 5567, December.
https://doi.org/10.1080/13675560701561789
Balcik, B., & Beamon, B.M., Krejci, C.C., Muramatsu, K.M., & Ramirez, M. (2010). Coordination in
humanitarian relief chains: Practices, challenges, and opportunities. International Journal of Production
Economics, 126(1), 22-34. https://doi.org/10.1016/j.ijpe.2009.09.008
Balcik, B., Beamon, B., & Smilowitz, K. (2008). Last Mile Distribution in Humanitarian Relief. Journal of
Intelligent Transportation Systems, 12(2), 51-63. https://doi.org/10.1080/15472450802023329
Balland, J. (2013). Humanitarian Relief Organizations and Its Relationship with Logistics Service Providers.Barbarosoğlu, G., & Arda, Y. (2004). A two-stage stochastic programming framework for transportation
planning in disaster response. Journal of the Operational Research Society, 55(1), 43-53.
https://doi.org/10.1057/palgrave.jors.2601652
Barbarosolu, G., Özdamar, L., & Çevik, A. (2002). An interactive approach for hierarchical analysis of
helicopter logistics in disaster relief operations. European Journal of Operational Research, 140(1), 118-133.
https://doi.org/10.1016/S0377-2217(01)00222-3
Barzinpour, F., & Esmaeili, V. (2014). A multi-objective relief chain location distribution model for urban
disaster management. International Journal of Advanced Manufacturing Technology, (70), 1291-1302.
https://doi.org/10.1007/s00170-013-5379-x
Battini, D., Peretti, U., Persona, A., & Sgarbossa, F. (2014). Application of humanitarian last mile
distribution model. Journal of Humanitarian Logistics and Supply Chain Management, 4(1), 131-148.
http://www.emeraldinsight.com/10.1108/JHLSCM-01-2013-0001 https://doi.org/10.1108/JHLSCM-01-2013-0001
Ben-Tal, A., Chung, B.D., Mandala, S.R., & Yao, T. (2011). Robust optimization for emergency logistics
planning: Risk mitigation in humanitarian relief supply chains. Transportation Research Part B:
Methodological, 45(8), 1177-1189. https://doi.org/10.1016/j.trb.2010.09.002
Berkoune, D., Renaud, J., Rekik, M., & Ruiz, A. (2012). Transportation in disaster response operations.
Socio-Economic Planning Sciences, 46(1), 23-32. https://doi.org/10.1016/j.seps.2011.05.002
Bozorgi-Amiri, A., Jabalameli, M.S., & Al-e-Hashem, S.M.J.M. (2013). A multi-objective robust stochastic
programming model for disaster relief logistics under uncertainty. OR Spectrum, 35(4), 905-933.
https://doi.org/10.1007/s00291-011-0268-x
Buzón, C.I.E. (2012). Distribución balanceada de ayuda humanitaria resuelto con un algoritmo metaheurístico. PhD
thesis. Tecnologico de Monterrey.
Campbell, A.M., & Jones, P.C. (2011). Prepositioning supplies in preparation for disasters. European Journal
of Operational Research, 209(2), 156-165. https://doi.org/10.1016/j.ejor.2010.08.029
Campbell, A.M., Vandenbussche, D., & Hermann, W. (2008). Routing for Relief Efforts. Transportation
Science, 127-145. https://doi.org/10.1287/trsc.1070.0209
Chern, C.C., Chen, Y.L., & Kung, L.C. (2010). A heuristic relief transportation planning algorithm for
emergency supply chain management. International Journal of Computer Mathematics, 87(7), 1638-1664.
https://doi.org/10.1080/00207160802441256Clark, 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 (Vol. 7). Atlantis Press. 233-257. http://eprints.uwe.ac.uk/17612/
https://doi.org/10.2991/978-94-91216-74-9_11
Cozzolino, A. (2012). Humanitarian Logistics: Cross-sector cooperation in disaster relief management. Springer.
https://doi.org/10.1007/978-3-642-30186-5
De Angelis, V., Mecoli, M., Nikoi, C., & Storchi, G. (2007). Multiperiod integrated routing and scheduling
of World Food Programme cargo planes in Angola. Computers and Operations Research, 34(6 Spec. Iss.),
1601-1615. https://doi.org/10.1016/j.cor.2005.07.012
Dolinskaya, I.S., Shi, Z.E., & Smilowitz, K.R. (2011). Decentralized Approaches to Logistics
Coordination in Humanitarian Relief. Proceeding of the 2011 Industrial Engineering Research Conference.
Edrissi, A., Nourinejad, M., & Roorda, M.J. (2015). Transportation network reliability in emergency
response. Transportation Research Part E: Logistics and Transportation Review, 80, 56-73.
http://linkinghub.elsevier.com/retrieve/pii/S1366554515001052 https://doi.org/10.1016/j.tre.2015.05.005
Egan, M.J. (2010). Private goods and services contracts: Increased emergency response capacity or
increased vulnerability? International Journal of Production Economics, 126(1), 46-56.
https://doi.org/10.1016/j.ijpe.2009.10.005
Görmez, N., Köksalan, M., & Salman, F. (2011). Locating disaster response facilities in Istanbul. Journal of
Operational Research Society, (62), 1239-1252. https://doi.org/10.1057/jors.2010.67
Gralla, E., Goentzel, J., & Fine, C. (2014). Assessing Trade-offs among Multiple Objectives for
Humanitarian Aid Delivery Using Expert Preferences. Production and Operations Management, 23(6),
978-989. https://doi.org/10.1111/poms.12110
Gu, Y. (2011). Research on Optimization of Relief Supplies Distribution Aimed to Minimize Disaster
Losses. Journal of Computers, 6(3), 603-609. https://doi.org/10.4304/jcp.6.3.603-609
Haghani, A., & Oh, S.C. (1996). Formulation and solution of a multi-commodity, multi-modal network
flow model for disaster relief operations. Transportation Research Part A: Policy and Practice, 30(3), 231-250.
https://doi.org/10.1016/0965-8564(95)00020-8
Heaslip, G. (2013). Services operations management and humanitarian logistics. Journal of Humanitarian
Logistics and Supply Chain Management, 5(1), 35-60. https://doi.org/10.1108/20426741311328501Heaslip, G., & Barber, E. (2014). Using the military in disaster relief: systemising challenges and
opportunities. Journal of Humanitarian Logistics and Supply Chain Management, 4(1), 60-81.
http://www.emeraldinsight.com/10.1108/JHLSCM-03-2013-0013 https://doi.org/10.1108/JHLSCM-03-2013-0013
Heaslip, G.E. (2012). The Logistical Challenges of Coordinating Military and Civilian Agencies in
Humanitarian Operations. Irish Academy of Management Conference, 353(0), 1-31.
Hong, J.-D., Jeong, K.-Y., & Feng, K. (2015). Emergency relief supply chain design and trade-off analysis.
Journal of Humanitarian Logistics and Supply Chain Management, 5(2), 162-187.
https://doi.org/10.1108/JHLSCM-05-2014-0019
Horner, M.W., & Downs, J.A. (2010). Optimizing hurricane disaster relief goods distribution: Model
development and application with respect to planning strategies. Disasters, 34(3), 821-844.
https://doi.org/10.1111/j.1467-7717.2010.01171.x
Horner, M.W., & Downs, J.A. (2007). Testing a Flexible Geographic Information System – Based
Network Flow Model for Routing Hurricane Disaster Relief Goods. Transportation Research Record: Journal
of the Transportation Research Board, 2022, 47-54. https://doi.org/10.3141/2022-06
Horner, M.W., & Widener, M.J. (2011). The effects of transportation network failure on people’s
accessibility to hurricane disaster relief goods: A modeling approach and application to a Florida case
study. Natural Hazards, 59, 1619-1634. https://doi.org/10.1007/s11069-011-9855-z
Hovhanessian, M. (2012). Coordination Barriers between Humanitarian Organizations and Commercial Agencies in
times of Disaster. Jönköping International Business School.
Hsueh, C.F., Chen, H.K., & Chou, H.W. (2008). Dynamic vehicle routing for relief logistics in natural
disasters. Vehicle Routing Problem. 71-84. https://doi.org/10.5772/5641
Huang, M., Smilowitz, K., & Balcik, B. (2012). Models for relief routing: Equity, efficiency, and efficacy.
Transportation Research Part E: Logistics and Transportation Review, 48(1), 2-18.
https://doi.org/10.1016/j.tre.2011.05.004
Huang, Y., Li, X., & Omitaomu, O. (2011). Conceptual Supernetwork Model for Coordination
Mechanisms in Humanitarian Relief Chain. In Doolen, T., & Van Aken, E. (Eds.). Proceedings of the 2011
Industrial Engineering Research Conference.
Jia, H., Ordoñez, F., & Dessouky, M.M. (2007). Solution approaches for facility location of medical
supplies for large-scale emergencies. Computers & Industrial Engineering, 52(2), 257-276.
https://doi.org/10.1016/j.cie.2006.12.007Kabra, G., Ramesh, A., & Arshinder, K. (2015). Identification and prioritization of coordination barriers
in humanitarian supply chain management. International Journal of Disaster Risk Reduction, 13, 128-138.
https://doi.org/10.1016/j.ijdrr.2015.01.011
Kovács, G., & Spens, K.M. (2007). Humanitarian logistics in disaster relief operations. International Journal
of Physical Distribution & Logistics Management, 37(2), 99-114. https://doi.org/10.1108/09600030710734820
Lin, Y. (2009). A logistics model for delivery of critical items in a disaster relief operation: heuristic
approaches †.
Lin, Y.H., Batta, R., Rogerson, P.A., Blatt, A., & Flanigan, M. (2011). A logistics model for emergency
supply of critical items in the aftermath of a disaster. Socio-Economic Planning Sciences, 45(4), 132-145.
https://doi.org/10.1016/j.seps.2011.04.003
McLachlin, R., & Larson, P.D. (2011). Building humanitarian supply chain relationships: lessons from
leading practitioners. Journal of Humanitarian Logistics and Supply Chain Mangement, 1(1), 32-49.
https://doi.org/10.1108/20426741111122402
Mete, H.O., & Zabinsky, Z.B. (2010). Stochastic optimization of medical supply location and
distribution in disaster management. Intern. Journal of Production Economics, 126(1), 76-84.
https://doi.org/10.1016/j.ijpe.2009.10.004
Moshtari, M., & Gonçalves, P. (2011). Understanding the drivers and barriers of coordination among
humanitarian organizations. POMS 23rd Annual Conference. Chicago, Illinois, USA.
Najafi, M., Eshghi, K., & Dullaert, W. (2013). A multi-objective robust optimization model for logistics
planning in the earthquake response phase. Transportation Research Part E, 49(1), 217-249.
https://doi.org/10.1016/j.tre.2012.09.001
Naji-Azimi, Z., Renaud, J., Ruiz, A., & Salari, M. (2012). A covering tour approach to the location of
satellite distribution centers to supply humanitarian aid. European Journal of Operational Research, 222(3),
596–605. https://doi.org/10.1016/j.ejor.2012.05.001
Nolz, P.C., Doerner, K.F., Gutjahr, W.J., & Hartl, R.F. (2010). A Bi-objective metaheuristic for disaster
relief operation planning. Studies in Computational Intelligence, 272, 167-187. https://doi.org/10.1007/978-3-642-
11218-8_8
Nolz, P.C., Doerner, K.F., & Hartl, R.F. (2010). Water distribution in disaster relief. International Journal of
Physical Distribution & Logistics Management, 40(8/9), 693-708. https://doi.org/10.1108/09600031011079337Noyan, N. (2012). Risk-averse two-stage stochastic programming with an application to disaster
management. Computers & Operations Research. 39(3), 541-559. https://doi.org/10.1016/j.cor.2011.03.017
Oh, S.C., & Haghani, A. (1997). Testing and evaluation of a multi-commodity multi-modal network flow
model for disaster relief management. Journal of Advanced Transportation, 31(3), 249-282.
https://doi.org/10.1002/atr.5670310304
Ortuño, M.T., Cristóbal, P., Ferrer, J.M., Martín-Campo, F.J., Muñoz, S., Tirado, G. et al. (2013). Decision
Aid Models and Systems for Humanitarian Logistics. A Survey. In Vitoriano, B., Montero, J., & Ruan, D.
(Eds.) Decision Aid Models for Disaster Management and Emergencies (Vol. 7). Spain: Atlantis Press.
https://doi.org/10.2991/978-94-91216-74-9_2
Özdamar, L., Ekinci, E., & Küçükyazici, B (2004). Emergency Logistics Planning in Natural Disasters.
Annals of Operations Research, 129(1-4), 217-245. https://doi.org/10.1023/B:ANOR.0000030690.27939.39
Özdamar, L., & Demir, O. (2012). A hierarchical clustering and routing procedure for large scale disaster
relief logistics planning. Transportation Research Part E: Logistics and Transportation Review, 48(3), 591-602.
http://www.sciencedirect.com/science/article/pii/S1366554511001396/pdfft?
md5=fb14cc103ee03ed39628a8d0f025c0fc&pid=1-s2.0-S1366554511001396-main.pdf
https://doi.org/10.1016/j.tre.2011.11.003
Pettit, S.J., Beresford, A.K.C., & Drive, C. (2007). Emergency relief logistics : an evaluation of military,
non-military and composite response models. International Journal of Logistics Research and Applications : A
Leading Journal of Supply Chain Management, 8(4), 313-331. https://doi.org/10.1080/13675560500407325
Rath, S., & Gutjahr, W.J. (2014). A math-heuristic for the warehouse location-routing problem in disaster
relief. Computers and Operations Research, 42, 25-39. https://doi.org/10.1016/j.cor.2011.07.016
Rawls, C.G., & Turnquist, M.A. (2010). Pre-positioning of emergency supplies for disaster response.
Transportation Research Part B, (44), 521-534. https://doi.org/10.1016/j.trb.2009.08.003
Rennemo, S.J., Rø, K.F., Hvattum, L.M., & Tirado, G. (2014). A three-stage stochastic facility routing model
for disaster response planning. Transportation Research Part E: Logistics and Transportation Review, 62, 116-135.
http://www.sciencedirect.com/science/article/pii/S1366554513002007/pdfft?
md5=c78a332ce6c8889eb284915f4422c602&pid=1-s2.0-S1366554513002007-main.pdf
https://doi.org/10.1016/j.tre.2013.12.006
Rottkemper, B., Fischer, K., & Blecken, A. (2012). A transshipment model for distribution and inventory
relocation under uncertainty in humanitarian operations. Socio-Economic Planning Sciences, (46), 98-109.
https://doi.org/10.1016/j.seps.2011.09.003
Saaty, T.L. (1980). The analytic hierarchy process. McGraw-Hill.Scholten, K., Scott, P.S., & Fynes, B. (2010). (Le) agility in humanitarian aid (NGO) supply chains.
International Journal of Physical Distribution Management, 40(8/9), 623-635.
https://doi.org/10.1108/09600031011079292
Schulz, S.F., & Blecken, A. (2010). Horizontal cooperation in disaster relief logistics: benefits and
impediments. International Journal of Physical Distribution & Logistics Management, 40(8/9), 636-656.
https://doi.org/10.1108/09600031011079300
Sheu, J.B. (2007). An emergency logistics distribution approach for quick response to urgent relief
demand in disasters. Transportation Research Part E: Logistics and Transportation Review, 43(6), 687-709.
https://doi.org/10.1016/j.tre.2006.04.004
Tatham, P., & Kovacs, G. (2010). The application of “swift trust” to humanitarian logistics. International
Journal of Production Economics, 126(1), 35-45. https://doi.org/10.1016/j.ijpe.2009.10.006
Tomasini, R.M., & Van Wassenhove, L.N. (2009). From preparedness to partnerships: case study research
on humanitarian logistics. International Transactions in Operational Research, 16(5), 549-559.
https://doi.org/10.1111/j.1475-3995.2009.00697.x
Tricoire, F., Graf, A., & Gutjahr, W.J. (2012). The bi-objective stochastic covering tour problem. Computers
& Operations Research, 39(7), 1582-1592. http://linkinghub.elsevier.com/retrieve/pii/S030505481100270X
https://doi.org/10.1016/j.cor.2011.09.009
Tzeng, G.-H., Cheng, H.-J., & Huang, T.D. (2007). Multi-objective optimal planning for designing relief
delivery systems. Transportation Research Part E: Logistics and Transportation Review, 43(6), 673-686.
https://doi.org/10.1016/j.tre.2006.10.012
Viswanath, K., & Peeta, S. (2003). Multicommodity Maximal Covering Network Design Problem for
Planning Critical Routes for Earthquake Response. Transportation Research Record.
https://doi.org/10.3141/1857-01
Vitoriano, B., Ortuño, M.T., & Tirado, G. (2009). HADS, a Goal Programming-Based Humanitarian Aid
Distribution System. Journal of Multi-Criteria Decision Analysis, (16), 55-64. https://doi.org/10.1002/mcda.439
Vitoriano, B., Ortuño, M.T., Tirado, G., & Montero, J. (2011). A multi-criteria optimization model for
humanitarian aid distribution. Journal of Global Optimization, 51(2), 189-208. https://doi.org/10.1007/s10898-
010-9603-z
Wohlgemuth, S., Oloruntoba, R., & Clausen, U. (2012). Dynamic vehicle routing with anticipation in
disaster relief. Socio-Economic Planning Sciences, (46), 261-271. https://doi.org/10.1016/j.seps.2012.06.001Yi, W., & Kumar, A. (2007). Ant colony optimization for disaster relief operations. Transportation Research
Part E: Logistics and Transportation Review, 43(6), 660-672. https://doi.org/10.1016/j.tre.2006.05.004
Yi, W., & Özdamar, L. (2007). A dynamic logistics coordination model for evacuation and support in
disaster response activities. European Journal of Operational Research, 179(3), 1177-1193.
https://doi.org/10.1016/j.ejor.2005.03.077
Yuan, Y., & Wang, D. (2009). Path selection model and algorithm for emergency logistics management.
Computers & Industrial Engineering, 56(3), 1081-1094. https://doi.org/10.1016/j.cie.2008.09.033
Zhan, S.L., & Liu, N. (2011). A multi-objective stochastic programming model for emergency logistics
based on goal programming. Proceedings - 4th International Joint Conference on Computational Sciences and
Optimization, CSO 2011. 640-644. https://doi.org/10.1109/CSO.2011.44
Zhang, X., Zhang, Z., Zhang, Y., Wei, D., & Deng, Y. (2013). Route selection for emergency logistics
management: A bio-inspired algorithm. Safety Science, 54, 87-91. https://doi.org/10.1016/j.ssci.2012.12.003
Zhu, C., & Ji, G. (2009). Emergency logistics and the distribution model for quick response to urgent
relief demand. Proceedings of the 2009 6th International Conference on Service Systems and Service Management,
ICSSSM ’09. 368-374.
Zografos, K.G., & Androutsopoulos, K.N. (2005). A decision support system for hazardous materials
transportation and emergency response management. 84th Annual Meeting of the Transportation Research
Board. Washington, D.C.
Jönköping University.

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