A Location-Routing Model for Assessment of the Injured People and Relief Distribution under Uncertainty

Document Type : Original Article

Authors

1 School of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran

2 Department of Industrial Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran

Abstract

Throughout history, nature has exposed humans to destructive phenomena such as earthquakes, floods, droughts, tornadoes, volcanic eruptions, and tropical and marine storms. The large scale of damages and casualties caused by natural disasters around the world has led to extensive applied research in the field of preparation and development of a comprehensive system for disaster management to minimize the resulting casualties and financial damages. Based on this motivation and challenges to the field, this research designs an integrated relief chain to optimize simultaneously the preparedness and response phases of disaster management. Decisions to improve the supply chain include locating distribution centers of relief supplies; the amount of inventory stored in facilities in pre-disaster phase, locating temporary care centers and transportation points of the injured, how to allocate relief services to the affected areas, and routing of the vehicles used to distribute relief supplies and evacuate the injured. The results show that decreasing the capacity of distribution centers increases the amount of shortage of supplies and increasing the capacity of these centers reduces the amount of shortage of supplies.

Keywords


8. REFERENCES
1. Paul, J. A. and Zhang, M., “Supply location and transportation planning for hurricanes: A two-stage stochastic programming framework”, European Journal of Operational Research, Vol. 274, No. 1, (2019), 108–125. doi:10.1016/j.ejor.2018.09.042
2. Paul, J. A. and Wang, X. (Jocelyn), “Robust location-allocation network design for earthquake preparedness”, Transportation Research Part B: Methodological, Vol. 119, (2019), 139–155. doi:10.1016/j.trb.2018.11.009
3. Loree, N. and Aros-Vera, F., “Points of distribution location and inventory management model for Post-Disaster Humanitarian Logistics”, Transportation Research Part E: Logistics and Transportation Review, Vol. 116, (2018), 1–24. doi:10.1016/j.tre.2018.05.003
4. Fathalikhani, S., Hafezalkotob, A., and Soltani, R., “Government intervention on cooperation, competition, and coopetition of humanitarian supply chains”, Socio-Economic Planning Sciences, Vol. 69, (2020). doi:10.1016/j.seps.2019.05.006
5. Cao, C., Li, C., Yang, Q., Liu, Y., and Qu, T., “A novel multi-objective programming model of relief distribution for sustainable disaster supply chain in large-scale natural disasters”, Journal of Cleaner Production, Vol. 174, (2018), 1422–1435. doi:10.1016/j.jclepro.2017.11.037
6. Davoodi, S. M. R. and Goli, A., “An integrated disaster relief model based on covering tour using hybrid Benders decomposition and variable neighborhood search: Application in the Iranian context”, Computers and Industrial Engineering, Vol. 130, (2019), 370–380. doi:10.1016/j.cie.2019.02.040
7. Noham, R. and Tzur, M., “Designing humanitarian supply chains by incorporating actual post-disaster decisions”, European Journal of Operational Research, Vol. 265, No. 3, (2018), 1064–1077. doi:10.1016/j.ejor.2017.08.042
8. Haghi, M., Fatemi Ghomi, S. M. T., and Jolai, F., “Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource”, Journal of Cleaner Production, Vol. 154, (2017), 188–202. doi:10.1016/j.jclepro.2017.03.102
9. Gu, J., Zhou, Y., Das, A., Moon, I.M., and Lee, G., “Medical relief shelter location problem with patient severity under a limited relief budget”, Computers and Industrial Engineering, Vol. 125, (2018), 720–728. doi:10.1016/j.cie.2018.03.027
10. Torabi, S. A., Shokr, I., Tofighi, S., and Heydari, J., “Integrated relief pre-positioning and procurement planning in humanitarian supply chains”, Transportation Research Part E: Logistics and Transportation Review, Vol. 113, (2018), 123–146. doi:10.1016/j.tre.2018.03.012
11. Hajiaghaei-Keshteli, M., Mohammadzadeha, H., and Fathollahi Fard, A. M., “New Approaches in Metaheuristics to Solve the Truck Scheduling Problem in a Cross-docking Center”, International Journal of Engineering, Transactions B: Applications, Vol. 31, No. 8, (2018), 1258–1266. doi:10.5829/ije.2018.31.08b.14
12. Nagurney, A., Salarpour, M., and Daniele, P., “An integrated financial and logistical game theory model for humanitarian organizations with purchasing costs, multiple freight service providers, and budget, capacity, and demand constraints”, International Journal of Production Economics, Vol. 212, (2019), 212–226. doi:10.1016/j.ijpe.2019.02.006
13. Liu, Y., Lei, H., Wu, Z., and Zhang, D., “A robust model predictive control approach for post-disaster relief distribution”, Computers and Industrial Engineering, Vol. 135, (2019), 1253–1270. doi:10.1016/j.cie.2018.09.005
14. Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., and Tavakkoli-Moghaddam, R., “A Lagrangian Relaxation-based Algorithm to Solve a Home Health Care Routing Problem”, International Journal of Engineering, Transactions, A: Basics, Vol. 31, No. 10, (2018), 1734–1740. doi:10.5829/ije.2018.31.10a.16
15. Abdalzaher, M. S. and Elsayed, H. A., “Employing data communication networks for managing safer evacuation during earthquake disaster”, Simulation Modelling Practice and Theory, Vol. 94, (2019), 379–394.
H. Beiki et al. / IJE TRANSACTIONS A: Basics Vol. 33, No. 7, (July 2020) 1274-1284 1283
doi:10.1016/j.simpat.2019.03.010
16. Abdi, A., Abdi, A., Fathollahi-Fard, A.M., and Hajiaghaei-Keshteli, M., “A set of calibrated metaheuristics to address a closed-loop supply chain network design problem under uncertainty”, International Journal of Systems Science: Operations and Logistics, (2019), 1–18. doi:10.1080/23302674.2019.1610197
17. Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M., Tian, G. and Li, Z., “An adaptive Lagrangian relaxation-based algorithm for a coordinated water supply and wastewater collection network design problem”, Information Sciences, Vol. 512, (2020), 1335–1359. doi:10.1016/j.ins.2019.10.062
18. Fathalikhani, S., Hafezalkotob, A., and Soltani, R., “Cooperation and coopetition among humanitarian organizations: A game theory approach”, Kybernetes, Vol. 47, No. 8, (2018), 1642–1663. doi:10.1108/K-10-2017-0369
19. Fu, Y., Tian, G., Fathollahi-Fard, A.M., Ahmadi, A. and Zhang, C., “Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint”, Journal of Cleaner Production, Vol. 226, (2019), 515–525. doi:10.1016/j.jclepro.2019.04.046
20. Tavana, M., Abtahi, A.R., Di Caprio, D., Hashemi, R. and Yousefi-Zenouz, R., “An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations”, Socio-Economic Planning Sciences, Vol. 64, (2018), 21–37. doi:10.1016/j.seps.2017.12.004
21. Safaeian, M., Fathollahi-Fard, A.M., Tian, G., Li, Z. and Ke, H., “A multi-objective supplier selection and order allocation through incremental discount in a fuzzy environment”, Journal of Intelligent and Fuzzy Systems, Vol. 37, No. 1, (2019), 1435–1455. doi:10.3233/JIFS-182843
22. Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., and Mirjalili, S., “A set of efficient heuristics for a home healthcare problem”, Neural Computing and Applications, Vol. 32, No. 10, (2020), 6185–6205. doi:10.1007/s00521-019-04126-8
23. Noyan, N. and Kahvecio─člu, G., “Stochastic last mile relief network design with resource reallocation”, OR Spectrum, Vol. 40, No. 1, (2018), 187–231. doi:10.1007/s00291-017-0498-7
24. Fathollahi-Fard, A.M., Govindan, K., Hajiaghaei-Keshteli, M. and Ahmadi, A., “A green home health care supply chain: New modified simulated annealing algorithms”, Journal of Cleaner Production, Vol. 240, (2019), 118200. doi:10.1016/j.jclepro.2019.118200
25. Li, H., Zhao, L., Huang, R., and Hu, Q., “Hierarchical earthquake shelter planning in urban areas: A case for Shanghai in China”, International Journal of Disaster Risk Reduction, Vol. 22, (2017), 431–446. doi:10.1016/j.ijdrr.2017.01.007
26. Bahadori-Chinibelagh, S., Fathollahi-Fard, A. M., and Hajiaghaei-Keshteli, M., “Two Constructive Algorithms to Address a Multi-Depot Home Healthcare Routing Problem”, IETE Journal of Research, (2019), 1–7. doi:10.1080/03772063.2019.1642802
27. Khojasteh, S. B. and Macit, I., “A Stochastic Programming Model for Decision-Making Concerning Medical Supply Location and Allocation in Disaster Management”, Disaster Medicine and Public Health Preparedness, Vol. 11, No. 6, (2017), 747–755. doi:10.1017/dmp.2017.9
28. Feng, Y., Zhang, Z., Tian, G., Fathollahi-Fard, A.M., Hao, N., Li, Z., Wang, W. and Tan, J., “A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise”, Applied Sciences, Vol. 9, No. 18, (2019), 3770. doi:10.3390/app9183770
29. Fathollahi-Fard, A. M., Niaz Azari, M., and Hajiaghaei-Keshteli, M., “An Improved Red Deer Algorithm to Address a Direct Current Brushless Motor Design Problem”, Scientia Iranica, (2019) doi:10.24200/sci.2019.51909.2419
30. Ghasemi, P., Khalili-Damghani, K., Hafezalkotob, A. and Raissi, S., “Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake)”, Socio-Economic Planning Sciences, Vol. 71, (2019) doi:10.1016/j.seps.2019.100745
31. Fathollahi-Fard, A.M., Ranjbar-Bourani, M., Cheikhrouhou, N. and Hajiaghaei-Keshteli, M., “Novel modifications of social engineering optimizer to solve a truck scheduling problem in a cross-docking system”, Computers and Industrial Engineering, Vol. 137, (2019). doi:10.1016/j.cie.2019.106103
32. Ghasemi, P., Khalili-Damghani, K., Hafezalkotob, A. and Raissi, S., “Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning”, Applied Mathematics and Computation, Vol. 350, (2019), 105–132. doi:10.1016/j.amc.2018.12.061
33. Torabi, N., Tavakkoli-Moghaddam, R. and Najafi, E., “A Two-Stage Green Supply Chain Network with a Carbon Emission Price by a Multi-objective Interior Search Algorithm”, International Journal of Engineering, Transactions C: Aspects, Vol. 32, No. 6, (2019), 828–834. doi:10.5829/ije.2019.32.06c.05
34. Mehranfar, N., Hajiaghaei-Keshteli, M., and Fathollahi-Fard, A. M., “A Novel Hybrid Whale Optimization Algorithm to Solve a Production-Distribution Network Problem Considering Carbon Emissions”, International Journal of Engineering, Transactions C: Aspects, Vol. 32, No. 12, (2019), 1781–1789. doi:10.5829/ije.2019.32.12c.11
35. Liu, X., Tian, G., Fathollahi-Fard, A.M. and Mojtahedi, M., “Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory”, Clean Technologies and Environmental Policy, Vol. 22, No. 2, (2020), 493–512. doi:10.1007/s10098-019-01798-7
36. Safaei, A. S., Farsad, S., and Paydar, M. M., “Robust bi-level optimization of relief logistics operations”, Applied Mathematical Modelling, Vol. 56, (2018), 359–380. doi:10.1016/j.apm.2017.12.003
37. Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., and Tavakkoli-Moghaddam, R., “The Social Engineering Optimizer (SEO)”, Engineering Applications of Artificial Intelligence, Vol. 72, (2018), 267–293. doi:10.1016/j.engappai.2018.04.009
38. Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., and Tavakkoli-Moghaddam, R., “Red deer algorithm (RDA): a new nature-inspired meta-heuristic”, Soft Computing, (2020), 1–29. doi:10.1007/s00500-020-04812-z
39. Fathollahi-Fard, A.M., Ahmadi, A., Goodarzian, F. and Cheikhrouhou, N.,, “A bi-objective home healthcare routing and scheduling problem considering patients’ satisfaction in a fuzzy environment”, Applied Soft Computing Journal, Vol. 93, (2020). doi:10.1016/j.asoc.2020.106385