Skip to main content
SpringerLink
Log in

A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty

  • Regular Article
  • Published:
OR Spectrum Aims and scope Submit manuscript

Abstract

Humanitarian relief logistics is one of the most important elements of a relief operation in disaster management. The present work develops a multi-objective robust stochastic programming approach for disaster relief logistics under uncertainty. In our approach, not only demands but also supplies and the cost of procurement and transportation are considered as the uncertain parameters. Furthermore, the model considers uncertainty for the locations where those demands might arise and the possibility that some of the pre-positioned supplies in the relief distribution center or supplier might be partially destroyed by the disaster. Our multi-objective model attempts to minimize the sum of the expected value and the variance of the total cost of the relief chain while penalizing the solution’s infeasibility due to parameter uncertainty; at the same time the model aims to maximize the affected areas’ satisfaction levels through minimizing the sum of the maximum shortages in the affected areas. Considering the global evaluation of two objectives, a compromise programming model is formulated and solved to obtain a non-dominating compromise solution. We present a case study of our robust stochastic optimization approach for disaster planning for earthquake scenarios in a region of Iran. Our findings show that the proposed model can help in making decisions on both facility location and resource allocation in cases of disaster relief efforts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Akkihal A (2006) Inventory pre-positioning for humanitarian operations. Thesis for Degree of Master of Engineering in Logistics, MIT CTL

  • Altay N, Green WG (2006) OR/MS research in disaster operations management. Eur J Oper Res 175(1): 475–493

    Article  Google Scholar 

  • Amiri A (2006) Designing a distribution network in a supply chain: formulation and efficient solution procedure. Eur J Oper Res 171: 567–576

    Article  Google Scholar 

  • Azaron A, Brown KN, Tarim SA, Modarres M (2008) A multiobjective stochastic programming approach for supply chain design considering risk. Int J Prod Econ 116: 129–138

    Article  Google Scholar 

  • Bakuli DL, Smith JM (1996) Resource allocation in state-dependent emergency evacuation networks. Eur J Oper Res 89(4): 543–555

    Article  Google Scholar 

  • Balcik B, Beamon BM (2008) Facility location in humanitarian relief. Int J Logist Res Appl 11(2): 101–121

    Article  Google Scholar 

  • Barbarosoglu G, Ozdamar L, Cevik A (2002) An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. Eur J Oper Res 140: 118–133

    Article  Google Scholar 

  • Barbarosoglu G, Arda Y (2004) A two-stage stochastic programming framework for transportation planning in disaster response. J Oper Res Soc 55: 43–53

    Article  Google Scholar 

  • Beamon BM, Kotleba SA (2006) Inventory modeling for complex emergencies in humanitarian relief operations. Int J Logist Res Appl 9(1): 1–18

    Google Scholar 

  • Beraldi P, Bruni ME, Conforti D (2004) Designing robust emergency medical service via stochastic programming. Eur J Oper Res 158(1): 183–193

    Article  Google Scholar 

  • Beraldi P, Bruni ME (2009) A probabilistic model applied to emergency service vehicle location. Eur J Oper Res 196(1): 323–331

    Article  Google Scholar 

  • Berberian M, Yeats RS (2001) Contribution of archaeological data to studies of earthquake history in the Iranian plateau. J Struct Geol 23: 563–584

    Article  Google Scholar 

  • Blecken A, Hellingrath B, Dangelmaier W, Schulz SF (2009) A humanitarian supply chain process reference model. Int J Serv Technol Manag 12(4): 391–413

    Article  Google Scholar 

  • Brotcorne L, Laporte G, Semet F (2003) Ambulance location and relocation models. Eur J Oper Res 147(3): 451–463

    Article  Google Scholar 

  • Campbell AM, Vandenbussche D, Hermann W (2008) Routing for relief efforts. Transp Sci 42(2): 127–145

    Article  Google Scholar 

  • Chang MS, Tseng YL, Chen JW (2007) A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transp Res Part E 43(6): 737–754

    Article  Google Scholar 

  • Cormican KJ, David P, Morton R, Kevin W (1998) Stochastic network interdiction. Oper Res 46(2): 184–197

    Article  Google Scholar 

  • Davis T (1993) Effective supply chain management. Sloan Manag Rev 34(4): 35–46

    Google Scholar 

  • Doerner KF, Hartl RF (2008) Health care logistics, emergency preparedness, and disaster relief: new challenges for routing problems with a focus on the Austrian situation. In: The vehicle routing problem: latest advances and new challenges, Part III. Springer, USA, pp 527–550

  • Fiedrich A, Gehbauer F, Rickers U (2000) Optimized resource allocation for emergency response after earthquake disasters. Saf Sci 35: 41–57

    Article  Google Scholar 

  • Haghani A, Afshar AM (2009) Supply chain management in disaster response. Final Project report, Department of Civil & Environmental Engineering, University of Maryland

  • Haghani A, Oh SC (1996) Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transp Res part A Pol 30(3): 231–250

    Article  Google Scholar 

  • Han LD, Yuan F, Chin SM, Hwang H (2006) Global optimization of emergency evacuation assignments. Interfaces 36(6): 502–513

    Article  Google Scholar 

  • Jafari MA (2010) Statistical prediction of the next great earthquake around Tehran, Iran. J Geodyn 49: 14–18

    Article  Google Scholar 

  • Jia H, Ordonez F, Dessouky M (2007a) A modeling framework for facility location of medical services for large-scale emergencies. IIE Trans 39(1): 41–55

    Article  Google Scholar 

  • Jia H, Ordonez F, Dessouky M (2007b) Solution approaches for facility location of medical supplies for large-scale emergencies. Comput Ind Eng 52(2): 257–276

    Article  Google Scholar 

  • Knott R (1987) The logistics of bulk relief suppliers. Disaster 11: 113–115

    Article  Google Scholar 

  • Knott R (1988) Vehicle routing for emergency relief management: a knowledge-based approach. Disaster 12: 285–293

    Article  Google Scholar 

  • Kovacs G, Spens KM (2007) Humanitarian logistics in disaster relief operations. Int J Phys Distrib Logist Manag 37(2): 99–114

    Article  Google Scholar 

  • Lodree EJ, Taskin S (2008) An insurance risk management framework for disaster relief and supply chain disruption inventory planning. J Oper Res Soc 59(5): 674–684

    Article  Google Scholar 

  • Mert A, Adivar BO (2010) Fuzzy disaster relief planning with credibility measures. In: 24th Mini EURO conference on Continuous optimization and information-based technologies in the financial sector, June 23–26, Izmir, Turkey

  • Mete ON, Zabinsky Z (2010) Stochastic optimization of medical supply distribution. Int J Prod Econ 126: 76–84

    Article  Google Scholar 

  • Mirzapour Al-e-hashem SMJ, Malekly H, Aryanezhad MB (2011) A multi-objective robust optimization model formulation product multi-site aggregate production planning in a supply chain under uncertainty. Int J Prod Econ. http://dx.doi.org/10.1016/j.ijpe.2011.01.027

  • Mulvey JM, Vanderbei RJ, Zenios SA (1995) Robust optimization of large-scale systems. Oper Res 43(2): 264–281

    Article  Google Scholar 

  • Nateghi AF (2001) Earthquake scenario for the mega-city of Tehran. Disaster Prev Manag 10(2): 95–100

    Article  Google Scholar 

  • Nazari H, Ritz JF, Salamati R, Solaymoni S, Balescu S, Michelot, JL, Ghassemi A, Talebian M, Lamothe M, Massaulut M (2007) Paleoseismological analysis in Central Alborz. In: 50th Anniversary earthquake Conference commemorating the 1957 Gobi-Altay earthquake (July–August 2007, Ulaanbaatar-Mongolia)

  • Nowroozi AA (2010) Probability of peak ground horizontal and peak ground vertical accelerations at Tehran and surrounding areas. Pure Appl Geophys 167: 1459–1474

    Article  Google Scholar 

  • Ozbay K, Ozguven EE (2007) Stochastic humanitarian inventory control model for disaster planning. Transp Res Rec 2022(1): 63–75

    Article  Google Scholar 

  • Ozdamar L, Ekinci E, Kucukyazici B (2004) Emergency logistics planning in natural disasters. Ann Oper Res 129(1–4): 217–245

    Article  Google Scholar 

  • Parentela E, Nambisan SS (2000) Emergency response (disaster management). In: Urban planning and development applications of GIS, ASCE, Reston, VA, pp 181–196

  • Rawls CG, Turnsquist MA (2010) Pre-positioning of emergency supplies for disaster response. Transp Res Part B Methodol 44(4): 521–534

    Article  Google Scholar 

  • Regnier E (2008) Public evacuation decisions and hurricane track uncertainty. Manag Sci 54(1): 16–28

    Article  Google Scholar 

  • Romero C, Tamiz M, Jones DF (1998) Goal programming, compromise programming and reference point method formulations: linkages and utility interpretations. J Oper Res Soc 49(9): 986–991

    Google Scholar 

  • Saadatseresht M, Mansourian A, Taleai M (2009) Evacuation planning using multi-objective evolutionary optimization approach. Eur J Oper Res 198: 305–314

    Article  Google Scholar 

  • Sakakibara H, Kajitani Y, Okada N (2004) Road network robustness for avoiding functional isolation in disasters. J Transp Eng ASCE 130: 560–567

    Article  Google Scholar 

  • Salmeron J, Apte A (2010) Stochastic optimization for natural disaster asset prepositioning. Prod Oper Manag 19(5): 561–574

    Article  Google Scholar 

  • Sheu JB (2007) An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transp Res Part E 43(6): 687–709

    Article  Google Scholar 

  • Sheu JB (2010) Dynamic relief-demand management for emergency logistics operations under large-scale disasters. Transp Res Part E 46: 1–17

    Article  Google Scholar 

  • Stepanov A, Smith JM (2009) Multi-objective evacuation routing in transportation networks. Eur J Oper Res 198: 435–446

    Article  Google Scholar 

  • Tomasini RM, Van Wassenhove LN (2004) Pan-American health organization’s humanitarian supply management system: de-politicization of the humanitarian supply chain by creating accountability. J Public Procur 4(3): 437–449

    Google Scholar 

  • Toregas C, Swain R, ReVelle C, Bergman L (1971) The location of emergency service facilities. Oper Res 19(6): 1363–1373

    Article  Google Scholar 

  • Tzeng GH, Cheng HJ, Huang TD (2007) Multi-objective optimal planning for designing relief delivery systems. Transp Res Part E 43(6): 673–686

    Article  Google Scholar 

  • Ukkusuri S, Yushimito W (2008) Location routing approach for the humanitarian prepositioning problem. Transp Res Rec 2089: 18–25

    Article  Google Scholar 

  • Van Wassenhove LN (2006) Humanitarian aid logistics: supply chain management in high gear. J Oper Res Soc 57(5): 475–489

    Article  Google Scholar 

  • Van Wassenhove LN, Martinez AJP, Stapleton O (2010) An Analysis of the relief supply chain in the first week after the Haiti earthquake. INSEAD Humanitarian Research Group. http://www.insead.edu/facultyresearch/centres/isic/documents/HaitiReliefSupplyChain_Final25Jan_.pdf

  • Viswanath K, Peeta S (2003) Multi-commodity maximal covering network design problem for planning critical routes for earthquake response. Transp Res Rec 1857: 1–10

    Article  Google Scholar 

  • Whybark DC (2007) Issues in managing disaster relief inventories. Int J Prod Econ 108(1–2): 228–235

    Article  Google Scholar 

  • Yi W, Kumar A (2007) Ant colony optimization for disaster relief operations. Transp Res Part E 43: 660–672

    Article  Google Scholar 

  • Yi W, Ozdamar L (2007) A dynamic logistics coordination model for evacuation and support in disaster response activities. Eur J Oper Res 179: 1177–1193

    Article  Google Scholar 

  • Yu CS, Li HL (2000) A robust optimization model for stochastic logistic problems. Int J Prod Econ 64(1–3): 385–397

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Iran University of Science and Technology, Narmak, 1684613114, Tehran, Iran

    Ali Bozorgi-Amiri, M. S. Jabalameli & S. M. J. Mirzapour Al-e-Hashem

Authors
  1. Ali Bozorgi-Amiri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. S. Jabalameli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. M. J. Mirzapour Al-e-Hashem
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ali Bozorgi-Amiri.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bozorgi-Amiri, A., Jabalameli, M.S. & Mirzapour Al-e-Hashem, S.M.J. A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR Spectrum 35, 905–933 (2013). https://doi.org/10.1007/s00291-011-0268-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00291-011-0268-x

Keywords

Search

Navigation