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Multi-objective, multi-period location-routing model to distribute relief after earthquake by considering emergency roadway repair

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Abstract

Natural disasters such as earthquakes impose destructive effects in the form of human injuries and damage to properties each year. Damage caused by the earthquake can disrupt traffic and highway systems, block vehicles and relief operations and make distribution operations difficult. Therefore, the repair of damaged roads in the least possible time so that distribution of relief can be done is a significant natural phenomenon after the disaster. In this study, a new mathematical integer nonlinear multi-objective, multi-period, multi-commodity model is suggested to locate the distribution centers, for timely distribution of vital relief to the damaged areas, vehicles routing and emergency roadway repair operations. It minimizes the travel time and total cost and increases reliability of the routes. To solve the designed problem, two meta-heuristic algorithms, namely non-dominated sorting genetic algorithm-II (NSGAII) and multi-objective particle swarm optimization (MOPSO), are offered. Then, the accuracy of mathematical models and efficiency of algorithms are assessed through numerical examples in detail.

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References

  1. Akkihal A (2006). Inventory pre-positioning for humanitarian operations. Thesis for degree of master of engineering in Logistics, MIT CTL

  2. Archeti C, Savelsbergh MWP, Speranza MG (2008) To split or not to split: that is the question. Transp Res Part E 44:114–123

    Article  Google Scholar 

  3. Aslanzadeh M, Rostami EA, Kardar L (2009) Logistics management and SCM in disasters. In: Supply chain and logistics in national, international and governmental environment. Physica-Verlag, pp 221–252

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

    Article  Google Scholar 

  5. Bozorgi-Amiri A, Khorsi M (2015) A dynamic multi-objective location-routing model for relief logistic planning under uncertainty on demand, travel time, and cost parameters. Int J Adv Manuf Technol. doi:10.1007/S00170-015-79233

    Google Scholar 

  6. Bozorgi-Amiri A, Jabalameli SMJ, Al-e-Hashem M (2013) A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR Spectr 35:905–933

    Article  MathSciNet  MATH  Google Scholar 

  7. Coello CAC, Pulido GT, Lechuga MS (2004) Handling multiple objectives with particle swarm optimization. IEEE Trans Evol Comput 8(3):256–279

    Article  Google Scholar 

  8. Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, Chichester

    MATH  Google Scholar 

  9. Eshghi K, Najafi M (2013) A logistics planning model to improve the response phase of earthquake. Int J Ind Eng Prod Manag 23:401–416

    Google Scholar 

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

    Article  Google Scholar 

  11. Ghodratnama A, Jolai F, Tavakkoli-Moghaddam R (2015) Solving a new multi-objective multi-route flexible flow line problem by multi-objective particle swarm optimization and NSGA-II. J Manuf Syst 36:189–202

    Article  Google Scholar 

  12. Govindan K, Jafarian A, Khodaverdi R, Devika K (2014) Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food. Int J Prod Econ 152:9–28

    Article  Google Scholar 

  13. Gulczynski D, Golden B, Wasil E (2011) The multi-depot split delivery vehicle routing problem: an integer programming-based heuristic, new test problems, and computational results. Comput Ind Eng 61(3):794–804

    Article  Google Scholar 

  14. Hanguang Q, Xumei Z (2006) Research on open location-routing problem based on improved particle swarm optimization algorithm. China Mech Eng 22:2356–2361

    Google Scholar 

  15. Huang SH (2015) Solving the multi-compartment capacitated location routing problem with pickup–delivery routes and stochastic demands. Comput Ind Eng 87:104–113

    Article  Google Scholar 

  16. Khalilpourazari S, Pasandideh SHR (2016) Multi-item EOQ model with nonlinear unit holding cost and partial backordering: moth-flame optimization algorithm. J Ind Prod Eng, 1–10

  17. Liberatore F, Ortuño MT, Tirado G, Vitoriano B, Scaparra MP (2014) A hierarchical compromise model for the joint optimization of recovery operations and distribution of emergency goods in Humanitarian Logistics. Comput Oper Res 42:3–13

    Article  MathSciNet  MATH  Google Scholar 

  18. Mete ON, Zabinsky Z (2010) Stochastic optimization of medical supply location and distribution in disaster management. Int J Prod Econ 126(1):76–84

    Article  Google Scholar 

  19. Mousavi SM, Sadeghi J, Niaki STA, Tavana M (2016) A bi-objective inventory optimization model under inflation and discount using tuned Pareto-based algorithms: NSGA-II, NRGA, and MOPSO. Appl Soft Comput 43:57–72

    Article  Google Scholar 

  20. Ozdamar L, Demir O (2012) A hierarchical clustering and routing procedure for large scale disaster relief logistics planning. Transp Res Part E 48(3):591–602

    Article  Google Scholar 

  21. Ozdamar L, Yi W (2007) A dynamic logistics coordination model for evacuation and support in disaster response activities. Eur J Oper Res 179(3):1177–1193

    Article  MathSciNet  MATH  Google Scholar 

  22. Rahdar MH, Heidari M, Ataei A, Choi JK (2016) Modeling and optimization of R-717 and R-134a ice thermal energy storage air conditioning systems using NSGA-II and MOPSO algorithms. Appl Therm Eng 96:217–227

    Article  Google Scholar 

  23. Sadeghi J, Sadeghi S, Niaki STA (2014) A hybrid vendor managed inventory and redundancy allocation optimization problem in supply chain management: an NSGA-II with tuned parameters. Comput Oper Res 41:53–64

    Article  MathSciNet  MATH  Google Scholar 

  24. Saydam C, Xiao J, Rajagopalan HK (2006) A multi period set- covering location model for dynamic redeployment of ambulances. Comput Oper Res 35(3):814–826

    MATH  Google Scholar 

  25. Setiawan E, French AP (2009) A location-allocation model for relief distribution and victim evacuation proceeding. Int Semin Ind Eng Manag

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

    Article  Google Scholar 

  27. Taguchi G (1987) System of experimental design; engineering methods to optimize quality and minimize costs (No. 04; QA279, T3.)

  28. Tajik N, Tavakkoli-Moghaddam R, Vahdani B, Mousavi SM (2014) A robust optimization approach for pollution routing problem with pickup and delivery under uncertainty. J Manuf Syst 33(2):277–286

    Article  Google Scholar 

  29. Talarico L, Meisel F, Sörensen K (2015) Ambulance routing for disaster response with patient groups. Comput Oper Res 56:120–133

    Article  MathSciNet  MATH  Google Scholar 

  30. Tavana M, Li Z, Mobin M, Komaki M, Teymourian E (2016) Multi-objective control chart design optimization using NSGA-III and MOPSO enhanced with DEA and TOPSIS. Expert Syst Appl 50:17–39

    Article  Google Scholar 

  31. Tofighi S, Torabi SA, Mansouri SA (2016) Humanitarian logistics network design under mixed uncertainty. Eur J Oper Res 250(1):239–250

    Article  MathSciNet  MATH  Google Scholar 

  32. 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 

  33. Vahdani B, Zandieh M (2010) Scheduling trucks in cross-docking systems: robust meta-heuristics. Comput Ind Eng 58(1):12–24

    Article  Google Scholar 

  34. Vahdani B, Tavakkoli-Moghaddam R, Zandieh M, Razmi J (2012) Vehicle routing scheduling using an enhanced hybrid optimization approach. J Intell Manuf 23(3):759–774

    Article  Google Scholar 

  35. Vincent FY, Lin SY (2015) A simulated annealing heuristic for the open location-routing problem. Comput Oper Res 62:184–196

    Article  MathSciNet  MATH  Google Scholar 

  36. Vitoriano B, Ortuno MT, Tirado G, Montero J (2011) A multi- criteria optimization model for humanitarian aid distribution. J Global Optim 51(2):189–208

    Article  MathSciNet  MATH  Google Scholar 

  37. Wang H, Du L, Ma S (2014) Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake. Transp Res Part E 69:160–179

    Article  Google Scholar 

  38. Yan S, Shih YL (2009) Optimal scheduling of emergency roadway repair and subsequent relief distribution. Comput Oper Res 36(6):2049–2065

    Article  MATH  Google Scholar 

  39. Yan S, Shih YL (2012) An ant colony system-based hybrid algorithm for an emergency roadway repair time-space network flow problem. Transportmetrica 8(5):361–386

    Article  Google Scholar 

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

    Article  Google Scholar 

  41. Zandieh M, Amiri M, Vahdani B, Soltani R (2009) A robust parameter design for multi-response problems. J Comput Appl Math 230(2):463–476

    Article  MathSciNet  MATH  Google Scholar 

  42. Zhan SL, Liu N, Ye Y (2014) Coordinating efficiency and equity in disaster relief logistics via information updates. Int J Syst Sci 45(8):1607–1621

    Article  MathSciNet  MATH  Google Scholar 

  43. Zhao J, Verter V (2015) A bi-objective model for the used oil location-routing problem. Comput Oper Res 62:157–168

    Article  MathSciNet  MATH  Google Scholar 

  44. Zokaee S, Bozorgi-Amiri A, Sadjadi SJ (2016) A robust optimization model for humanitarian relief chain design under uncertainty. Appl Math Model

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Correspondence to Behnam Vahdani.

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Vahdani, B., Veysmoradi, D., Shekari, N. et al. Multi-objective, multi-period location-routing model to distribute relief after earthquake by considering emergency roadway repair. Neural Comput & Applic 30, 835–854 (2018). https://doi.org/10.1007/s00521-016-2696-7

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  • DOI: https://doi.org/10.1007/s00521-016-2696-7

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