Skip to main content

Advertisement

Log in

Optimizing Locations and Scales of Emergency Warehouses Based on Damage Scenarios

  • Published:
Journal of the Operations Research Society of China Aims and scope Submit manuscript

Abstract

Choosing the locations and the capacities of emergency warehouses for the storage of relief materials is critical to the quality of services provided in the wake of a large-scale emergency such as an earthquake. This paper proposes a stochastic programming model to determine disaster sites’ locations as well as their scales by considering damaged scenarios of the facility and by introducing seismic resilience to describe the ability of disaster sites to resist earthquakes. The objective of the model is to minimize fixed costs of building emergency warehouses, expected total transportation costs under uncertain demands of disaster sites and penalty costs for lack of relief materials. A local branching (LB) based solution method and a particle swarm optimization (PSO) based solution method are proposed for the problem. Extensive numerical experiments are conducted to assess the efficiency of the heuristic according to the real data of Yunnan province in China.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Boonmee, C., Arimura, M., Asada, T.: Facility location optimization model for emergency humanitarian logistics. Int. J. Disaster Risk Reduct. 24, 485–498 (2017)

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  5. Yushimito, W.F., Jaller, M., Ukkusuri, S.: A voronoi-based heuristic algorithm for locating distribution centers in disasters. Netw. Spat. Econ. 12(1), 21–39 (2010)

    Article  MathSciNet  Google Scholar 

  6. Haghani, A., Oh, S.C.: Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transp. Res. Part A Policy Pract. 30, 231–250 (1996)

    Article  Google Scholar 

  7. Barbarosoǧlu, G., Arda, Y.: A two-stage stochastic programming framework for transportation planning in disaster response. J. Oper. Res. Soc. 55(1), 43–53 (2004)

    Article  Google Scholar 

  8. Tzeng, G.H., Cheng, H.J., Huang, T.D.: Multi-objective optimal planning for designing relief delivery systems. Transp. Res. Part E Logist. Transp. Rev. 43(6), 673–686 (2007)

    Article  Google Scholar 

  9. Cui, T., Ouyang, Y., Shen, Z.J.M.: Reliable facility location design under the risk of disruptions. Oper. Res. 58(4-part-1), 998–1011 (2010)

    Article  MathSciNet  Google Scholar 

  10. Rath, S., Gutjahr, W.J.: A math-heuristic for the warehouse location–routing problem in disaster relief. Comput. Oper. Res. 42, 25–39 (2014)

    Article  MathSciNet  Google Scholar 

  11. Abounacer, R., Rekik, M., Renaud, J.: An exact solution approach for multi-objective location–transportation problem for disaster response. Comput. Oper. Res. 41, 83–93 (2014)

    Article  MathSciNet  Google Scholar 

  12. Zhen, L., Wang, K., Liu, H.C.: Disaster relief facility network design in metropolises. IEEE Trans. Syst. Man Cybern. Syst. 45, 751–761 (2015)

    Article  Google Scholar 

  13. Caunhye, A.M., Zhang, Y., Li, M., Nie, X.: A location-routing model for prepositioning and distributing emergency supplies. Transp. Res. Part E Logist. Transp. Rev. 90, 161–176 (2016)

    Article  Google Scholar 

  14. Zhen, L.: Tactical berth allocation under uncertainty. Eur. J. Oper. Res. 247(3), 928–944 (2015)

    Article  MathSciNet  Google Scholar 

  15. Salman, F.S., Yücel, E.: Emergency facility location under random network damage: insights from the Istanbul case. Comput. Oper. Res. 62, 266–281 (2015)

    Article  MathSciNet  Google Scholar 

  16. Verma, A., Gaukler, G.M.: Pre-positioning disaster response facilities at safe locations: an evaluation of deterministic and stochastic modeling approaches. Comput. Oper. Res. 62, 197–209 (2015)

    Article  MathSciNet  Google Scholar 

  17. Yu, G., Haskell, W.B., Liu, Y.: Resilient facility location against the risk of disruptions. Transp. Res. Part B Methodol. 104, 82–105 (2017)

    Article  Google Scholar 

  18. Qu, X., Wang, S., Zhang, J.: On the fundamental diagram for freeway traffic: a novel calibration approach for single-regime models. Transp. Res. Part B Methodol. 73, 91–102 (2015)

    Article  Google Scholar 

  19. Moreno, A., Alem, D., Ferreira, D.: Heuristic approaches for the multiperiod location-transportation problem with reuse of vehicles in emergency logistics. Comput. Oper. Res. 69, 79–96 (2016)

    Article  MathSciNet  Google Scholar 

  20. Wang, S., Meng, Q.: Liner shipping network design with deadlines. Comput. Oper. Res. 41, 140–149 (2014)

    Article  MathSciNet  Google Scholar 

  21. Wang, S., Meng, Q.: Robust bunker management for liner shipping networks. Eur. J. Oper. Res. 243(3), 789–797 (2015)

    Article  MathSciNet  Google Scholar 

  22. Zhang, Y., Snyder, L.V., Qi, M., Miao, L.: A heterogeneous reliable location model with risk pooling under supply disruptions. Transp. Res. Part B Methodol. 83, 151–178 (2016)

    Article  Google Scholar 

  23. Fischetti, M., Lodi, A.: Local branching. Math. Program. 98(1–3), 23–47 (2003)

    Article  MathSciNet  Google Scholar 

  24. Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: Sixth International Symposium on Micro Machine and Human Science, MHS, pp. 39–43 (1995)

  25. Yapicioglu, H., Smith, A.E., Dozier, G.: Solving the semi-desirable facility location problem using bi-objective particle swarm. Eur. J. Oper. Res. 177(2), 733–749 (2007)

    Article  Google Scholar 

  26. Bruneau, M., Chang, S.E., Eguchi, R.T., Lee, G.C., O’Rourke, T.D., Reinhorn, A.M., Shinozuka, M., Tierney, K., Wallace, W.A., von Winterfeldt, D.: A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq. Spectra 19(4), 733–752 (2003)

    Article  Google Scholar 

  27. Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst. Man Cybern. Syst. 15, 116–132 (1985)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shu-Min Lin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, BC., Li, M., Hu, Y. et al. Optimizing Locations and Scales of Emergency Warehouses Based on Damage Scenarios. J. Oper. Res. Soc. China 8, 437–456 (2020). https://doi.org/10.1007/s40305-018-0215-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40305-018-0215-5

Keywords

Mathematics Subject Classification

Navigation