A mathematical model for business sector participation in relief logistics

Document Type : Research Paper


School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran


Humanitarian organizations are in the dire need of logistical resources for relief operations. Nevertheless, considering their limited resources, they have to seek to use the logistical capabilities of the business sector in order to improve the humanitarian operations. In this paper, we develop a bi-objective mathematical model for using the logistical capabilities of the business sector in the humanitarian logistics. The first objective function minimizes the logistics costs while the second one minimizes the shortage costs. We consider that suppliers are responsible for procurement of relief items and logistics service providers collaborate with a humanitarian organization by providing storage space for pre-positioning of relief items. The bi-objective model is converted into a single-objective one using the TH method as a well-known interactive fuzzy multi-objective programming approach. Finally, the presented model is validated by conducting several sensitivity analyses. The results emphasis on the effectiveness of collaborating with business sector in relief operations.


Main Subjects

Abolfazli, N., Eshghali, M., Ghomi, S.F., (2022). Pricing and coordination strategy for green supply chain under two production modes, 2022 Systems and Information Engineering Design Symposium (SIEDS). IEEE, pp. 13-18.
Aghajani, M., Torabi, S.A., (2019). A mixed procurement model for humanitarian relief chains. Journal of Humanitarian Logistics and Supply Chain Management.
Aghajani, M., Torabi, S.A., Heydari, J., (2020). A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains. Socio-Economic Planning Sciences 71, 100780.
Akbarpour, M., Torabi, S.A., Ghavamifar, A., (2020). Designing an integrated pharmaceutical relief chain network under demand uncertainty. Transportation Research Part E: Logistics and Transportation Review 136, 101867.
Arcala Hall, R., (2008). Civil-military cooperation in international disaster response: the Japanese Self-Defense Forces’ deployment in Aceh, Indonesia. The Korean Journal of Defense Analysis 20(4), 383-400.
Bai, X., Gao, J., Liu, Y., (2018). Prepositioning emergency supplies under uncertainty: A parametric optimization method. Engineering Optimization 50(7), 1114-1133.
Balcik, B., Ak, D., (2014). Supplier selection for framework agreements in humanitarian relief. Production and Operations Management 23(6), 1028-1041.
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.
Balcik, B., Silvestri, S., Rancourt, M.È., Laporte, G., (2019). Collaborative prepositioning network design for regional disaster response. Production and Operations Management 28(10), 2431-2455.
Bealt, J., Barrera, J.C.F., Mansouri, S.A., (2016). Collaborative relationships between logistics service providers and humanitarian organizations during disaster relief operations. Journal of Humanitarian Logistics and Supply Chain Management.
Bui, T., Cho, S., Sankaran, S., Sovereign, M., (2000). A framework for designing a global information network for multinational humanitarian assistance/disaster relief. Information Systems Frontiers 1(4), 427-442.
Carland, C., Goentzel, J., Montibeller, G., (2018). Modeling the values of private sector agents in multi-echelon humanitarian supply chains. European Journal of Operational Research 269(2), 532-543.
Chen, J., Chen, T.H.Y., Vertinsky, I., Yumagulova, L., Park, C., (2013). Public–private partnerships for the development of disaster resilient communities. Journal of contingencies and crisis management 21(3), 130-143.
Chen, Y., Zhao, Q., Huang, K., Xi, X., (2022). A Bi-objective optimization model for contract design of humanitarian relief goods procurement considering extreme disasters. Socio-Economic Planning Sciences 81, 101214.
Coles, J.B., Zhang, J., Zhuang, J., (2018). Partner selection in disaster relief: Partnership formation in the presence of incompatible agencies. International journal of disaster risk reduction 27, 94-104.
Desi-Nezhad, Z., Sabouhi, F., Dehghani Sadrabadi, M.H., (2022). An optimization approach for disaster relief network design under uncertainty and disruption with sustainability considerations. RAIRO--Operations Research 56(2).
Diabat, A., Jabbarzadeh, A., Khosrojerdi, A., (2019). A perishable product supply chain network design problem with reliability and disruption considerations. International Journal of Production Economics 212, 125-138.
Dufour, É., Laporte, G., Paquette, J., Rancourt, M.È., (2018). Logistics service network design for humanitarian response in East Africa. Omega 74, 1-14.
Eshkiti, A., Bozorgi-Amiri, A., Sabouhi, F., (2022). A bi-objective mathematical model to respond to COVID-19 pandemic. Journal of Industrial and Systems Engineering 14(3), 221-236.
Fahimnia, B., Jabbarzadeh, A., Ghavamifar, A., Bell, M., (2015). Supply chain design for efficient and effective blood supply in disasters. International Journal of Production Economics.
Fikar, C., Gronalt, M., Hirsch, P., (2016). A decision support system for coordinated disaster relief distribution. Expert Systems with Applications 57, 104-116.
Ghavamifar, A., Sabouhi, F., Makui, A., (2018). An integrated model for designing a distribution network of products under facility and transportation link disruptions. Journal of Industrial and Systems Engineering 11(1), 113-126.
Ghavamifar, A., Torabi, S.A., (2022). OR/MS Models for the Humanitarian-Business Partnership, The Palgrave Handbook of Operations Research. Springer, pp. 835-858.
Ghavamifar, A., Torabi, S.A., Moshtari, M., (2022). A hybrid relief procurement contract for humanitarian logistics. Transportation Research Part E: Logistics and Transportation Review 167, 102916.
Guan, P., Zhang, J., Payyappalli, V.M., Zhuang, J., (2018). Modeling and validating public–private partnerships in disaster management. Decision Analysis 15(2), 55-71.
Horwitz, S., (2009). Wal-Mart to the rescue: Private enterprise's response to Hurricane Katrina. The Independent Review 13(4), 511-528.
Hu, S., Dong, Z.S., (2019). Supplier selection and pre-positioning strategy in humanitarian relief. Omega 83, 287-298.
Jahre, M., Jensen, L.M., (2010). Coordination in humanitarian logistics through clusters. International Journal of Physical Distribution & Logistics Management.
Kandler, K., Siller, J., (2022). Humanitarian Logistics: The Outsourcing Collaboration with Logistics Service Providers in the UN System.
Kapucu, N., (2008). Collaborative emergency management: better community organising, better public preparedness and response. Disasters 32(2), 239-262.
Kaur, H., Singh, S.P., (2022). Disaster resilient proactive and reactive procurement models for humanitarian supply chain. Production Planning & Control 33(6-7), 576-589.
Kucukaltan, B., Irani, Z., Acar, A.Z., (2022). Business model canvas for humanitarian operations of logistics service providers. Production Planning & Control 33(6-7), 590-605.
Li, X., Ramshani, M., Huang, Y., (2018). Cooperative maximal covering models for humanitarian relief chain management. Computers & industrial engineering 119, 301-308.
Lieb, R.C., Millen, R.A., Van Wassenhove, L.N., (1993). Third party logistics services: a comparison of experienced American and European manufacturers. International Journal of Physical Distribution & Logistics Management.
Lu, Y., Yang, C., Yang, J., (2022). A multi-objective humanitarian pickup and delivery vehicle routing problem with drones. Annals of Operations Research, 1-63.
Maghsoudi, A., Moshtari, M., (2020). Challenges in disaster relief operations: evidence from the 2017 Kermanshah earthquake. Journal of Humanitarian Logistics and Supply Chain Management.
Makui, A., Ghavamifar, A., (2016). Benders Decomposition Algorithm for Competitive Supply Chain Network Design under Risk of Disruption and Uncertainty. Journal of Industrial and Systems Engineering 9, 30-50.
Maldonado, E.A., Maitland, C.F., Tapia, A.H., (2010). Collaborative systems development in disaster relief: The impact of multi-level governance. Information Systems Frontiers 12(1), 9-27.
Maon, F., Lindgreen, A., Vanhamme, J., (2009). Developing supply chains in disaster relief operations through cross‐sector socially oriented collaborations: a theoretical model. Supply chain management: an international journal.
Mavrotas, G., Florios, K., (2013). An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems. Applied Mathematics and Computation 219(18), 9652-9669.
Nurmala, N., de Leeuw, S., Dullaert, W., (2017). Humanitarian–business partnerships in managing humanitarian logistics. Supply Chain Management: An International Journal.
Parragh, S.N., Tricoire, F., Gutjahr, W.J., (2022). A branch-and-Benders-cut algorithm for a bi-objective stochastic facility location problem. Or Spectrum 44(2), 419-459.
Rawls, C.G., Turnquist, M.A., (2010). Pre-positioning of emergency supplies for disaster response. Transportation research part B: Methodological 44(4), 521-534.
Rodríguez-Espíndola, O., Albores, P., Brewster, C., (2018). Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods. European Journal of Operational Research 264(3), 978-993.
Rodríguez‐Pereira, J., Balcik, B., Rancourt, M.È., Laporte, G., (2021). A cost‐sharing mechanism for multi‐country partnerships in disaster preparedness. Production and Operations Management 30(12), 4541-4565.
Sabbaghtorkan, M., Batta, R., He, Q., (2020). Prepositioning of assets and supplies in disaster operations management: Review and research gap identification. European Journal of Operational Research 284(1), 1-19.
Sabouhi, F., Bozorgi-Amiri, A., Vaez, P., (2020). Stochastic optimization for transportation planning in disaster relief under disruption and uncertainty. Kybernetes.
Sabouhi, F., Jabalameli, M.S., (2019). A stochastic bi-objective multi-product programming model to supply chain network design under disruption risks. Journal of Industrial and Systems Engineering 12(3), 196-209.
Shehadeh, K.S., Tucker, E.L., (2022). Stochastic optimization models for location and inventory prepositioning of disaster relief supplies. Transportation Research Part C: Emerging Technologies 144, 103871.
Simatupang, T.M., Sridharan, R., (2005). An integrative framework for supply chain collaboration. The international Journal of Logistics management 16(2), 257-274.
Stewart, G.T., Kolluru, R., Smith, M., (2009). Leveraging public‐private partnerships to improve community resilience in times of disaster. International Journal of Physical Distribution & Logistics Management.
Taleizadeh, A.A., Ghavamifar, A., Khosrojerdi, A., (2020). Resilient network design of two supply chains under price competition: game theoretic and decomposition algorithm approach. Operational Research, 1-33.
Tomasini, R.M., (2018). The Evolutions of Humanitarian-Private Partnerships: Collaborative Frameworks Under Review, The Palgrave Handbook of Humanitarian Logistics and Supply Chain Management. Springer, pp. 627-635.
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.
Torabi, S.A., Hassini, E., (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy sets and systems 159(2), 193-214.
Torabi, S.A., Shokr, I., Tofighi, S., Heydari, J., (2018). Integrated relief pre-positioning and procurement planning in humanitarian supply chains. Transportation Research Part E: Logistics and Transportation Review 113, 123-146.
Turkeš, R., Cuervo, D.P., Sörensen, K., (2019). Pre-positioning of emergency supplies: does putting a price on human life help to save lives? Annals of Operations Research 283(1), 865-895.
Vahdani, B., Veysmoradi, D., Noori, F., Mansour, F., (2018). Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. International journal of disaster risk reduction 27, 290-306.
Wachtendorf, T., Kendra, J.M., (2004). Considering convergence, coordination, and social capital in disasters.
Wang, Q., Liu, Z., Jiang, P., Luo, L., (2022). A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition. Socio-Economic Planning Sciences, 101279.
Wang, Q., Nie, X., (2022). A stochastic programming model for emergency supply planning considering transportation network mitigation and traffic congestion. Socio-Economic Planning Sciences 79, 101119.
Zhang, M., Kong, Z., (2022). A multi-attribute double auction and bargaining model for emergency material procurement. International Journal of Production Economics, 108635.
Zhu, T., Boyles, S.D., Unnikrishnan, A., (2022). Two-stage robust facility location problem with drones. Transportation Research Part C: Emerging Technologies 137, 103563.