Distribution planning of relief commodities considering the features of demand areas: A robust multi-objective approach

Document Type : Article


Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran


Logistics planning plays an important role in providing services to the disaster -stricken areas. In this study, a scenario-based multi-objective model is presented to locate the distribution and evacuation centers and distribute the relief commodities with an appropriate allocation. It aims to serve the earthquake-stricken areas that are classified according to their construction qualities. The objective functions of cost, responsiveness and demand coverage are considered in the proposed optimization model. Moreover, due to the uncertain nature of a disaster and uncertainty in some model parameters, a robust optimization approach is utilized. A revised multi-choice goal programming method is applied to solve the multi-objective model. The proposed model is validated through a case study conducted in the city of Amol. The computational results show the efficiency of the proposed model in a real–world disaster situation.


Main Subjects

1. Van Wassenhove, L.N. \Humanitarian aid logistics:
supply chain management in high gear", Journal of
the Operational Research Society, 57(5), pp. 475-489
2. Goudie, A.S., The Human Impact on the Natural
Environment: Past, Present, and Future, John Wiley
and Sons (2013).
3. Guha-Sapir, D., Below, R. and Hoyois. Ph., EM-DAT:
the CRED/OFDA International Disaster Database,
Universite Catholique de Louvain, Brussels, Belgium
4. Cyganik, K.A. \Disaster preparedness in Virginia hospital
center-Arlington after Sept 11, 2001", Disaster
Management & Response, 1(3), pp. 80-86 (2003).
5. Balcik, B. and Beamon, B.M. \Facility location in humanitarian
relief", International Journal of Logistics,
11(2), pp. 101-121 (2008).
3792 M.M. Paydar et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3776{3793
6. Thomas, A., Humanitarian Logistics, Enabling Disaster
Response, The Handbook of Fritz Institute (2003).
7. Brotcorne, L., Laporte, G., and Semet, F. \Ambulance
location and relocation models", European Journal of
Operational Research, 147(3), pp. 451-463 (2003).
8. Van Wassenhove, L.N. and Pedraza Martinez, A.J.
\Using OR to adapt supply chain management best
practices to humanitarian logistics", International
Transactions in Operational Research, 19(1-2), pp.
307-322 (2012).
9. Altay, N. and Green, W.G. \OR/MS research in
disaster operations management", European Journal of
Operational Research, 175(1), pp. 475-493 (2006).
10. Toregas, C., Swain, R., ReVelle, C., and Bergman, L.
\The location of emergency service facilities", Operations
Research, 19(6), pp. 1363-1373 (1971).
11. Alcada-Almeida, L., Tralhao, L., Santos, L., and
Coutinho-Rodrigues, J. \A multi objective approach to
locate emergency ECs and identify evacuation routes
in urban areas", Geographical Analysis, 41(1), pp. 9-29
12. Mete, H.O. and Zabinsky, Z.B. \Stochastic optimization
of medical supply location and distribution in
disaster management", International Journal of Production
Economics, 126(1), pp. 76-84 (2010).
13. Rawls, C.G. and Turnquist, M.A. \Pre-positioning
planning for emergency response with service quality
constraints", OR Spectrum, 33(3), pp. 481-498 (2011).
14. Caunhye, A.M., Nie, X., and Pokharel, S. \Optimization
models in emergency logistics: A literature
review", Socio-economic Planning Sciences, 46(1), pp.
4-13 (2012).
15. Bozorgi-Amiri, A., Jabalameli, M.S., and Al-e-
Hashem, S.M. \A multi-objective robust stochastic
programming model for disaster relief logistics under
uncertainty", OR Spectrum, 35(4), pp. 905-933 (2013).
16. Davis, L.B., Samanlioglu, F., Qu, X., and Root,
S. \Inventory planning and coordination in disaster
relief e orts", International Journal of Production
Economics, 141(2), pp. 561-573 (2013).
17. Naja , M., Eshghi, K., and Dullaert, W. \A multiobjective
robust optimization model for logistics planning
in the earthquake response phase", Transportation
Research, Part E: Logistics and Transportation
Review, 49(1), pp. 217-249 (2013).
18. Barzinpour, F. and Esmaeili, V. \A multi-objective relief
chain location distribution model for urban disaster
management", The International Journal of Advanced
Manufacturing Technology, 70(5-8), pp. 1291-1302
19. Rezaei-Malek, M. and Tavakkoli-Moghaddam, R. \Robust
humanitarian relief logistics network planning",
Uncertain Supply Chain Management, 2(2), pp. 73-96
20. Abounacer, R., Rekik, M., and Renaud, J. \An
exact solution approach for multi-objective locationtransportation
problem for disaster response", Computers
& Operations Research, 41, pp. 83-93 (2014).
21. Hu, S.L., Han, C.F., and Meng, L.P. \A scenario
planning approach for propositioning rescue centers
for urban waterlog disasters", Computers & Industrial
Engineering, 87, pp. 425-435 (2015).
22. Givler, A.E. and Mitchell, J.E. \A fair division approach
to humanitarian logistics incorporating conditional
value-at-risk", Annals of Operations Research,
262(1), pp. 133-151 (2018).
23. Bozorgi-Amiri, A. and Khorsi, M. \A dynamic multiobjective
location-routing model for relief logistic planning
under uncertainty on demand, travel time, and
cost parameters", The International Journal of Advanced
Manufacturing Technology, 85(5-8), pp. 1633-
1648 (2016).
24. Gutjahr W.J. and Dzubur, N. \Bi-objective bi-level
optimization of distribution center locations considering
user equilibria", Transportation Research, Part E:
Logistics and Transportation Review, 31(85), pp. 1-22
25. Zokaee, S., Bozorgi-Amiri, A., and Sadjadi, S.J. \A
robust optimization model for humanitarian relief
chain design under uncertainty", Applied Mathematical
Modeling, 40(17), pp. 7996-8016 (2016).
26. 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, 154, pp. 188-
202 (2017).
27. Shishebori, D., and Babadi, A.Y. \Robust and reliable
medical services network design under uncertain environment
and system disruptions", Transportation Research,
Part E: Logistics and Transportation Review,
77, pp. 268-288 (2015).
28. Moreno, A., Alem, D., and Ferreira, D. \Heuristic approaches
for the multi period location-transportation
problem with reuse of vehicles in emergency logistics",
Computers & Operations Research, 69, pp. 79-96
29. Rezaei-Malek, M. and Tavakkoli-Moghaddam, R., Zahiri,
B., and Bozorgi-Amiri, A. \An interactive approach
for designing a robust disaster relief logistics
network with perishable commodities", Computers &
Industrial Engineering, 94, pp. 201-215 (2016).
30. Ben-Tal, A., El Ghaoui, L. and Nemirovski, A., Robust
Optimization. Princeton Series in Applied Mathematics,
The Handbook of Princeton University Press
M.M. Paydar et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3776{3793 3793
31. Ben-Tal, A., El Ghaoui, L., and Nemirovski, A.
\Foreword: special issue on robust optimization",
Mathematical Programming, 107(1), pp. 1-3 (2006).
32. Mulvey, J.M., Vanderbei, R.J. and Zenios, S.A. \Robust
optimization of large-scale systems", Operations
Research, 43(2), pp. 264-281 (1995).
33. Yu, C.S. and Li, H.L. \A robust optimization model
for stochastic logistic problems", International Journal
of Production Economics, 64(1), pp. 385-397 (2000).
34. Charnes, A., Cooper, W.W., and Ferguson, R.O.
\Optimal estimation of executive compensation by
linear programming", Management Science, 1(2), pp.
138-151 (1955).
35. Charnes, A. and Cooper, W.W. \Management models
and industrial applications of linear programming",
Management Science, 4(1), pp. 38-91 (1957).
36. Chang, C.T. \Multi-choice goal programming",
Omega, 35(4), pp. 389-396 (2007).
37. Dilley, Maxx., Natural Disaster Hotspots: A Global
Risk Analysis, 5, World Bank Publications (2005).
38. Nabavi, S.M. \Historical earthquakes in Iran, 300BC-
1900 AD", Journal of Earth and Space Physics, 7(1),
pp. 70-117 (1978).
39. Abe, K. \Magnitudes of large shallow earthquakes
from 1904 to 1980", Physics of the Earth and Planetary
Interiors, 27(1), pp. 72-92 (1981).