Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains

Transportation Research Part B: Methodological

Volumn 45, Issue 8, 2011, Pages 1177-1189

  Ben Tal, Aharon ^a   Chung, Byung Do ^b   Mandala, Supreet Reddy ^b   Yao, Tao ^b  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^b The Pennsylvania State University   (United States)

Author keywords

Demand uncertainty; Dynamic traffic assignment; Emergency logistics; Robust optimization

Indexed keywords

EMERGENCY TRAFFIC CONTROL; OPTIMIZATION; STOCHASTIC PROGRAMMING; STOCHASTIC SYSTEMS; SUPPLY CHAINS;

AFFINELY-ADJUSTABLE ROBUST COUNTERPART; CELL TRANSMISSION MODEL; DEMAND UNCERTAINTY; DYNAMIC OPTIMIZATION PROBLEM (DOP); DYNAMIC TRAFFIC ASSIGNMENTS; EMERGENCY LOGISTICS; ROBUST OPTIMIZATION; TIME-DEPENDENT DEMAND;

TRAFFIC CONTROL;

COMPUTER SIMULATION; DEMAND ANALYSIS; HUMANITARIAN AID; LOGISTICS; OPTIMIZATION; RISK ASSESSMENT; SAMPLING; TRAFFIC MANAGEMENT; TRANSPORTATION PLANNING;

EID: 80051945761     PISSN: 01912615     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trb.2010.09.002     Document Type: Article

References (45)

1. Atamturk A., Zhang M. Two-stage robust network flow and design under demand uncertainty. Operations Research - Baltimore 2007, 55(4):662-673.
2. Ben-Tal A., Boyd S., Nemirovski A. Extending scope of robust optimization: comprehensive robust counterparts of uncertain problems. Mathematical Programming 2006, 107(1):63-89.
3. Ben-Tal A., El Ghaoui L., Nemirovski A. Robust Optimization 2009, Princeton University Press.
4. Ben-Tal A., Goryashko A., Guslitzer E., Nemirovski A. Adjustable robust solutions of uncertain linear programs. Mathematical Programming 2004, 99(2):351-376.
5. Ben-Tal A., Nemirovski A. Robust convex optimization. Mathematics of Operations Research 1998, 23(4):769-805.
6. Ben-Tal A., Nemirovski A. Robust solutions of uncertain linear programs. Operations Research Letters 1999, 25(1):1-14.
7. Ben-Tal A., Nemirovski A. Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming 2000, 88(3):411-424.
8. Ben-Tal A., Nemirovski A. Robust optimization - methodology and applications. Mathematical Programming 2002, 92(3):453-480.
9. Bertsimas, D., Brown, D.B., Caramanis, C., 2007. Theory and Applications of Robust Optimization. Submitted. http://users.ece.utexas.edu/cmcaram/pubs/RobustOptimizationLV.pdf.
10. Bertsimas, D., Perakis, G., 2005. Robust and adaptive optimization: a tractable approach to optimization under uncertainty. NSF/CMMI/OR 0556106.
11. Bertsimas D., Sim M. Robust discrete optimization and network flows. Mathematical Programming 2003, 98(1):49-71.
12. Bertsimas D., Sim M. The price of robustness. Operations Research 2004, 52(1):35-53.
13. Chiu Y.C., Zheng H., Villalobos J., Gautam B. Modeling no-notice mass evacuation using a dynamic traffic flow optimization model. IIE Transactions 2007, 39(1):83-94.
14. Daganzo C.F. The cell transmission model. Part I: a simple dynamic representation of highway traffic. Transportation Research B 1993, 28(2):269-287.
15. Daganzo C.F. The cell transmission model, part II: network traffic. Transportation Research Part B 1995, 29(2):79-93.
16. El Ghaoui L., Oks M., Oustry F. Worst-case value-at-risk and robust portfolio optimization: a conic programming approach. Operations Research 2003, 51(4):543-556.
17. El Ghaoui L., Oustry F., AitRami M. A cone complementarity linearization algorithm for static output-feedback and related problems. IEEE Transactions on Automatic Control 1997, 42(8):1171-1176.
18. Erera A.L., Morales J.C., Savelsbergh M. Robust optimization for empty repositioning problems. Operations Research 2009, 57(2):468-483.
19. Friesz T.L., Bernstein D. Handbook of transport modelling. Analytical dynamic traffic assignment models 2000, Pergamon, pp. 181-195.
20. Guha-Sapir, D., Debarati, G.S., Hargitt, D., Hoyois, P., Below, R., Brechet, D., 2004. Thirty Years of Natural Disasters 1974-2003: The Numbers. Presses Univ. de Louvain.
21. Karoonsoontawong A., Waller S.T. Robust dynamic continuous network design problem. Transportation Research Record: Journal of the Transportation Research Board 2007, 2029(-1):58-71.
22. Lindell M.K. EMBLEM2: an empirically based large scale evacuation time estimate model. Transportation Research Part A 2008, 42:140-154.
23. Lodree E.J., Taskin S. An insurance risk management framework for disaster relief and supply chain disruption inventory planning. Journal of the Operational Research Society 2008, 59(5):674-684.
24. Merchant D.K., Nemhauser G.L. A model and an algorithm for the dynamic traffic assignment problems. Transportation Science 1978, 12(3):183.
25. Merchant D.K., Nemhauser G.L. Optimality conditions for a dynamic traffic assignment model. Transportation Science 1978, 12(3):200.
26. Mudchanatongsuk S., Ordonez F., Liu J. Robust solutions for network design under transportation cost and demand uncertainty. Journal of the Operational Research Society 2008, 59(5):652-662.
27. Mulvey J.M., Vanderbei R.J., Zenios S.A. Robust optimization of large-scale systems. Operations Research 1995, 43(2):264-281.
28. Nie, Y., 2010. A Cell-based Merchant-Nemhauser Model for the System Optimum Dynamic Traffic Assignment Problem. Transportation Research Board 89th Annual Meeting.
29. Ordóñez F., Zhao J. Robust capacity expansion of network flows. Networks 2007, 50(2):136-145.
30. Ozdamar L., Ekinci E., Kucukyazici B. Emergency logistics planning in natural disasters. Annals of Operations Research 2004, 129(1):217-245.
31. Peeta S., Zhou C. Robustness of the off-line a priori stochastic dynamic traffic assignment solution for on-line operations. Transportation Research Part C 1999, 7(5):281-303.
32. Peeta S., Ziliaskopoulos A.K. Foundations of dynamic traffic assignment: the past, the present and the future. Networks and Spatial Economics 2001, 1(3):233-265.
33. Radwan A.E., Hobeika A.G., Sivasailam D. A computer simulation model for rural network evacuation under natural disasters. ITE Journal 1985, 55(9):25-30.
34. Shapiro A. Monte Carlo sampling methods. Handbooks in Operations Research and Management Science 2003, 10:353-426.
35. Shapiro A., Nemirovski A. On Complexity of Stochastic Programming Problems 2005, Springer.
36. Sheu J.B. An emergency logistics distribution approach for quick response to urgent relief demand in disasters. Transportation Research Part E 2007, 43(6):687-709.
37. Tuydes, H., 2005. Network Traffic Management under Disaster Conditions. Ph.D. Thesis, Northwestern University, Evanston, IL.
38. Ukkusuri S.V., Waller S.T. Linear programming models for the user and system optimal dynamic network design problem: formulations, comparisons and extensions. Networks and Spatial Economics 2008, 8(4):383-406.
39. Waller S.T., Schofer J.L., Ziliaskopoulos A.K. Evaluation with traffic assignment under demand uncertainty. Transportation Research Record: Journal of the Transportation Research Board 2001, 1771:69-74.
40. Waller S.T., Ziliaskopoulos A.K. A chance-constrained based stochastic dynamic traffic assignment model: analysis, formulation and solution algorithms. Transportation Research Part C 2006, 14(6):418-427.
41. Xie C., Lin D.Y., Travis Waller S. A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies. Transportation Research Part E 2010, 46(3):295-316.
42. Yazici M.A., Ozbay K. Impact of probabilistic road capacity constraints on the spatial distribution of hurricane evacuation shelter capacities. Transportation Research Record: Journal of the Transportation Research Board 2007, 2022:55-62.
43. Yin Y., Lawphongpanich S., Lou Y. Estimating investment requirement for maintaining and improving highway systems. Transportation Research Part C 2008, 16(2):199-211.
44. Yin Y., Madanat S.M., Lu X.Y. Robust improvement schemes for road networks under demand uncertainty. European Journal of Operational Research 2009, 198(2):470-479.
45. Ziliaskopoulos A.K. A linear programming model for the single destination system optimum dynamic traffic assignment problem. Transportation Science 2000, 34(1):37-49.