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A modified particle swarm optimization for disaster relief logistics under uncertain environment

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Abstract

Relief logistics is one of the most important elements of a relief operation. This paper investigates a relief chain design problem where 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 can arise and the possibility that a number of the facility could be partially destroyed by the disaster. The proposed model for this study is formulated as a mixed-integer nonlinear programming to minimize the sum of the expected total cost (which includes costs of location, procurement, transportation, holding, and shortage) and the variance of the total cost. The model simultaneously determines the location of relief distribution centers and the allocation of affected area to relief distribution centers. Furthermore, an efficient solution approach based on particle swarm optimization is developed in order to solve the proposed mathematical model. At last, computational results for several instances of the problem are presented to demonstrate the feasibility and effectiveness of the proposed model and algorithm.

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References

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

    Article  MATH  Google Scholar 

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

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  5. Drezner T, Drezner Z, Salhi S (2006) A multi-objective heuristic approach for the casualty collection points location problem. J Oper Res Soc 57:727–734

    Article  MATH  Google Scholar 

  6. Doerner KF, Gutjahr WJ, Nolz PC (2009) Multi-criteria location planning for public facilities in tsunami-prone coastal areas. OR Spectr 31:651–678

    Article  MathSciNet  MATH  Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

  9. Balcik B, Beamon BM (2008) Facility location in humanitarian relief. International Journal of Logistics Research and Applications 11(2):101–121

    Article  Google Scholar 

  10. Berman O, Drezner Z, Wesolowsky GO (2007) The transfer point location problem. Eur J Oper Res 179:978–989

    Article  MathSciNet  MATH  Google Scholar 

  11. Berman O, Drezner Z, Wesolowsky GO (2008) The multiple location of transfer points. J Oper Res Soc 59:805–811

    Article  MATH  Google Scholar 

  12. Sherali HD, Carter TB, Hobeika AG (1991) A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions. Transportation Research Part B 25(6):439–452

    Article  Google Scholar 

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

    Article  Google Scholar 

  14. Beamon BM, Kotleba SA (2006) Inventory modeling for complex emergencies in humanitarian relief operations. International Journal of Logistics: Research and Applications 9(1):1–18

    Google Scholar 

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

    Article  Google Scholar 

  16. 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  MATH  Google Scholar 

  17. Haghani A, Oh SC (1996) Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transport Research Part A 30(3):231–250

    Article  Google Scholar 

  18. 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 

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

    Article  MathSciNet  Google Scholar 

  20. Barbarosoglu G, Ozdamar L, Cevik A (2002) An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal Operation Research 140:118–133

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  22. Yi W, Kumar A (2007) Ant colony optimization for disaster relief operations. Transportation Research Part E 43:660–672

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  25. Yuan Y, Wang D (2008) Path selection model and algorithm for emergency logistics management. Comput Ind Eng 56:1081–1094

    Article  Google Scholar 

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

    Article  Google Scholar 

  27. 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  MathSciNet  MATH  Google Scholar 

  28. Ozdamar L, Yi W (2008) Greedy neighborhood search for disaster relief and evacuation logistics. IEEE Intelligent Systems 14–23.

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

    Article  MathSciNet  Google Scholar 

  30. Chiou YC, Lai YH (2008) An integrated multi-objective model to determine the optimal rescue path and traffic controlled arcs for disaster relief operations under uncertainty environments. J Adv Transp 42(4):493–519

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  34. Peidro D, Mula J, Poler R, Lario FC (2009) Quantitative models for supply chain planning under uncertainty: a review. Int J Adv Manuf Technol 43:400–420

    Article  Google Scholar 

  35. 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  MATH  Google Scholar 

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

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  38. Salmeron J, Apte A (2009) Stochastic optimization for natural disaster asset prepositioning. Prod Oper Manag 19(5):561–574

    Article  Google Scholar 

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

    Article  Google Scholar 

  40. Rawls CG, Trunquist MA (2010) Pre-positioning of emergency supplies for disaster response. Transportation research part B: Methodological 44(4):521–534

    Article  Google Scholar 

  41. Azaron A, Borwn KN, Tarim SA, Modarres M (2008) A multi-objective stochastic programming approach for supply chain design considering risk. Int J Prod Econ 116:129–138

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  43. Baohua W, Shiwei HE (2009) Robust optimization model and algorithm for logistics center location and allocation under uncertain environment. Journal of Transportation Systems Engineering and Information Technology 9(2):69–74

    Article  Google Scholar 

  44. Pan F, Nagi R (2010) Robust supply chain design under uncertain demand in agile manufacturing. Comput Oper Res 37(4):668–683

    Article  MATH  Google Scholar 

  45. 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 

  46. Megiddo N, Supowit KJ (1984) On the complexity of some common geometric location problems. SIAM J Comput 13:182–196

    Article  MathSciNet  MATH  Google Scholar 

  47. Kennedy J, Eberhart R (1995) Particle swarm optimization. In Proceedings of IEEE International Conference on Neural Networks 4:1942–1948

    Article  Google Scholar 

  48. Clerc M, Kennedy J (2002) The particle swarm—explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evol Comput 6(1):58–73

    Article  Google Scholar 

  49. Kennedy J, Eberhart R (1997) A discrete binary version of the particle swarm algorithm, In Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, Orlando, 4104–4108.

  50. Kennedy J, Eberhart RC, Shi Y (2001) Swarm intelligence. Morgan Kaufmann, San Francisco, CA

    Google Scholar 

  51. Wang S, Watada J (2010) A hybrid modified PSO approach to VaR-based facility location problems with variable capacity in fuzzy random uncertainty, Information Sciences (in press)

  52. Zhi J, Liu JY, Wang W, Wu HP, Gao J (2010) Logistics center location selection based on the algorithm of hybrid particle swarm optimization. Key Engineering Materials 439–440:429–433

    Article  Google Scholar 

  53. Marinakis Y, Marinaki M (2009) A particle swarm optimization algorithm with path relinking for the location routing problem. Journal of Mathematical Model Algorithm 7:59–78

    Article  MathSciNet  Google Scholar 

  54. Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization: an overview. Swarm Intelligent 1:33–57

    Article  Google Scholar 

  55. Banks A, Vincent J, Anyakoha C (2007) A review of particle swarm optimization. Part I: background and development. Nat Comput 6:467–484

    Article  MathSciNet  MATH  Google Scholar 

  56. Banks A, Vincent J, Anyakoha C (2008) A review of particle swarm optimization. Part II_ hybridization, combinatorial, multi-criteria and constrained optimization, and indicative applications. Nat Comput 7:109–124

    Article  MathSciNet  MATH  Google Scholar 

  57. Safaei N, Saidi-Mehrabad M, Jabal-Ameli MS (2008) A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. Eur J Oper Res 185:563–592

    Article  MATH  Google Scholar 

  58. Cordeau JF, Laporte G, Mercier A (2001) A unified tabu search heuristic for vehicle routing problems with time windows. J Oper Res Soc 52:928–936

    Article  MATH  Google Scholar 

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Authors and Affiliations

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

    Ali Bozorgi-Amiri, Mohammad Saeid Jabalameli, Mehdi Alinaghian & Mahdi Heydari

  2. Iran University of Science and Technology, Narmak–Tehran, P.C.1684613114, Iran

    Ali Bozorgi-Amiri

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  1. Ali Bozorgi-Amiri
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  2. Mohammad Saeid Jabalameli
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  3. Mehdi Alinaghian
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  4. Mahdi Heydari
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Correspondence to Ali Bozorgi-Amiri.

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Bozorgi-Amiri, A., Jabalameli, M.S., Alinaghian, M. et al. A modified particle swarm optimization for disaster relief logistics under uncertain environment. Int J Adv Manuf Technol 60, 357–371 (2012). https://doi.org/10.1007/s00170-011-3596-8

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