Document Type : Original Article
Associate Professor, Shahrood University of Technology.
In this study, a robust two-stage risk-aversion optimization model is proposed for the multi-product relief network design problem. The comprehensive set of decisions for locating and reinforcing relief facilities, inventory planning, and distributing healthcare items has been considered in an integrated manner. Uncertainties of relief facility capacity, relief demand, and the node linkage capacity are considered. Moreover, the weighted average expected loss is considered in the proposed robust planning model. The efficiency of the proposed model has been evaluated by examining numerical instances. The obtained results indicate the efficiency of the distributionally robust model compared to the traditional two-stage stochastic model. In addition, the type of ambiguous set and levels of confidence, risk aversion, and adjustment parameters will affect network performance.
- Ahmadi, M., Seifi, A. & Tootooni, B. (2015). A Humanitarian Logistics Model for Disaster Relief Operation Considering Network Failure and Standard Relief Time: A Case Study On San Francisco District. Res. Part E: Logist. Transp. Rev., 75, 145–163.
- Akgun, İ., Gumuşbuğa, F. & Tansel, B. (2015). Risk Based Facility Location By Using Fault Tree Analysis in Disaster Management. Omega, 52, 168-179.
- Akkihal, A. R. (2004). Inventory Pre-positioning for Humanitarian Operations M.Sc. Thesis, Massachusetts Institute of Technology.
- Altay, N., & Green, W. G. (2006). Or/Ms Research in Disaster Operations Management. European Journal of Operational Research, 175, 475–493.
- Anaya-Arenas, A. M., Renaud, J. & Ruiz, A. (2014). Relief Distribution Networks: A Systematic Review. Annals of Operations Research, 223, 1–27.
- Aydin, N. (2016). A Stochastic Mathematical Model to Locate Field Hospitals under Disruption Uncertainty for Large-Scale Disaster Preparedness. An International Journal of Optimization and Control: Theories & Applications, 6, 85-102.
- 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.
- Berman, O., Krass, D. & Menezes, M. B. C. (2007). Facility Reliability Issues In Network P-Median Problems: Strategic Centralization and Co-Location Effects. Operations Research, 55, 332–50.
- Bertsimas, D. & Sim, M. (2004). The Price of Robustness. Operations Research, 52(1), 35-53.
- Bozorgi-Amiri, A., Jabalameli, M. S., Alinaghian, M. & Heydari, M. (2012). A Modified Particle Swarm Optimization for Disaster Relief Logistics under Uncertain Environment. J. Adv. Manuf. Technol., 60, 357–371.
- Caunhye, A. M., Nie, X. & Pokharel, S. (2012). Optimization Models in Emergency Logistics: A Literature Review. -Econ. Plan. Sci., 46, 4–13.
- Doerner, K. F., Gutjahr, W. J. & Nolz, P. C. (2009). Multi-Criteria Location Planning For Public Facilities in Tsunami-Prone Coastal Areas. Or Spectrum, 31, 651-678.
- Döyen, A., Aras, N. & Barbarosoglu, G. (2012). A Two-Echelon Stochastic Facility Location Model for Humanitarian Relief Logistics. Lett., 6, 1123–1145.
- Galindo, G. & Batta, R. (2013). Review of Recent Developments in Or/Ms Research in Disaster Operations Management. European Journal of Operational Research, 230, 201–211.
- Garrido, R. A., Lamas, P. & Pino, F. J. (2014). A Stochastic Programming Approach for Floods Emergency Logistics. Transp. Res. Part E: Logist. Rev., 75, 18–31.
- Hasani, A. (2015). Marketing Strategies Selection for Supply Chain Management under Uncertainty Propagation. Journal of Industrial Management Perspective, 5(2), 33-62 (In Persian).
- Hasani, A., Hosseini, S. (2015). A Comprehensive Robust Bi-objective Model and a Memetic Solution Algorithm for Designing Reverse Supply Chain Network under Uncertainty. Journal of Industrial Management Perspective, 4(4), 31-54. (In Persian)
- Hasani, A., Mokhtari, (2018). Redesign strategies of a comprehensive robust relief network for disaster management. Socio-Economic Planning Sciences, 64, 92-102.
- Hasani, A., & Mokhtari, H. (2019). An integrated relief network design model under uncertainty: A case of Iran. Safety Science, 111, 22-36.
- Hasanpour, J., Hasani, A., & Ghodoosi, M. (2018). Delayed Payment Policy in the Inventory Model of Deteriorating Goods with Quadratic Demand in Order to Backlogging Shortage. Journal of Industrial Management Perspective, 7(4), 199-230. (In Persian)
- Ikeda, Y. & Inoue, M. (2016). An Evacuation Route Planning for Safety Route Guidance System after Natural Disaster Using Multi-objective Genetic Algorithm. Computer Science, 96, 1323-1331.
- Jia, H., Ordóñez, F. & Dessouky, M. M. (2007a). A Modeling Framework for Facility Location of Medical Services for Large-Scale Emergencies. IIE transactions, 39, 41-55.
- Jia, H., Ordóñez, F. & Dessouky, M. M. (2007b). Solution Approaches for Facility Location of Medical Supplies for Large-Scale Emergencies. Computers & Industrial Engineering, 52, 257-276.
- Kılcı, F., Kara, B. Y. & Bozkaya, B. (2015). Locating Temporary Shelter Areas after an Earthquake: A Case for Turkey. European Journal of Operational Research, 243, 323-332.
- Lu, C. C. & Sheu, J. B. (2013). Robust Vertex P-Center Model for Locating Urgent Relief Distribution Centers. Computers & Operations Research, 40, 2128-2137.
- Ma, L., Liu, Y., & Liu, Y. (2020). Distributionally Robust Design for Bicycle-Sharing Closed-Loop Supply Chain Network under Risk-Averse Criterion. Journal of Cleaner Production, 246,
- Mete, H. O. & Zabinsky, Z. B. (2010). Stochastic Optimization of Medical Supply Location and Distribution in Disaster Management. International Journal of Production Economics, 126, 76–84.
- Mulvey; J.M., Vanderbei, R.J., & Zenios, S.A. (1995). Robust Optimization of Large-Scale Systems. Operations Research, 43, 2, 264-281.
- Noyan, N. (2012). Risk-averse two-stage stochastic programming with an application to disaster management. Computers & Operations Research, 39(3), 541-
- Onan, K., Ülengin, F. & Sennaroğlu, B. (2015). An Evolutionary Multi-Objective Optimization Approach to Disaster Waste Management: A Case Study of Istanbul, Turkey. In Expert Systems with Applications, 42, 8850-8857.
- Özdamar, L. & Ertem, M. A. (2015). Models, Solutions and Enabling Technologies in Humanitarian Logistics. J. Oper. Res., 244, 55–65.
- Rawls, C. G. & Turnquist, M. A. 2010. Pre-Positioning of Emergency Supplies for Disaster Response. Res. Part B: Methodol, 44, 521–534.
- Rockafellar, R. T., & Uryasev, S. (2000). Optimization of conditional value at risk. Journal of Risk, 3(3), 21-
- Sabouhi, F., Heydari, M. & Bozorgi-Amiri, A. (2016). Multi-Objective Routing and Scheduling For Relief Distribution with Split Delivery in Post-Disaster Response. Journal of Industrial and Systems Engineering, 9, 17-27.
- Snyder, L. V. & Daskin, M. S. (2005). Reliability Models for Facility Location: The Expected Failure Cost Case. Transportation Science, 39, 400–16.
- Tofighi, S. (2011). A Logistics Planning Model and Solution Method in Humanitarian Relief Chains. Sc Thesis, University of Tehran.