Risk approaches for delivering disaster relief supplies

Springer Science and Business Media LLC - Tập 33 - Trang 543-569 - 2011
Pamela C. Nolz1,2, Frédéric Semet3, Karl F. Doerner2,4
1Ecole des Mines de Saint-Etienne, CMP Georges Charpak, Gardanne, France
2Department of Business Administration, University of Vienna, Vienna, Austria
3Ecole Centrale de Lille, LAGIS, Cité Scientifique, Villeneuve d’Ascq, France
4Institute of Production and Logistics Management, Johannes Kepler University Linz, Linz, Austria

Tóm tắt

We consider the problem of designing the logistic system to assure adequate distribution of relief aid in a post-natural-disaster situation, when damages to infrastructure may disrupt the delivery of relief aid. The problem is formulated as a multi-objective optimization problem, encompassing three objective functions of central interest in such problems. The first objective function is a measure of risk (various forms of such risk are analyzed). The second objective function measures the coverage provided by the logistic system in the distribution of relief aid to disaster victims. The third objective function represents total travel time. We focus on the risk of delivery tours for relief supplies, where risk here captures the threat that potential tours become impassable after the natural hazard event. In order to cope with a range of different natural disasters and policy objectives, we develop five approaches emphasizing different measures of tour-dependent risk. To cover both earthquake and flood risks, we consider correlated as well as uncorrelated risk measures. We develop a two-phase solution approach to reflect the dictates of real-world disaster relief motivating this analysis. The first phase generates potentially Pareto-optimal solutions to the overall multi-objective logistic design problem with respect to three objectives. For any given risk measure, the first-phase design problem is formulated as a multi-objective integer program and a memetic algorithm is proposed as the solution approach. The second phase is an enrichment procedure to generate a broader range of potentially Pareto-optimal alternatives. The suggested approach is tested on real-world data from the province of Manabí in Ecuador and the results associated with the different risk measures are analyzed to illustrate the value of the proposed approach for the design of disaster relief networks.

Tài liệu tham khảo

Altay N, Green WG (2006) OR/MS research in disaster operations management. Eur J Oper Res 175(1): 475–493 Balcik B, Beamon B, Smilowitz K (2008) Last mile distribution in humanitarian relief. J Intell Transp Syst 12: 51–63 Barbarosoglu G, Özdamar L, Cevik A (2002) An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. Eur J Oper Res 140: 118–133 Campbell AM, Vandenbussche D, Hermann W (2008) Routing for relief efforts. Transp Sci 42(2): 127–145 Clímaco JCN, Pascoal MMB (2009) Finding non-dominated bicriteria shortest pairs of disjoint simple paths. Comput Oper Res 39(11): 2892–2898 De Angelis V, Mecoli M, Nikoi C, Storchi G (2007) Multiperiod integrated routing and scheduling of World Food Programme cargo planes in Angola. Comput Oper Res 34: 1601–1615 Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2): 182–197 Doerner K, Focke A, Gutjahr W (2007) Multicriteria tour planning for mobile healthcare facilities in a developing country. Eur J Oper Res 179: 1078–1096 Fortz B (2000) Design of survivable networks with bounded rings. Kluwer Academic Publishers, Dordrecht Gandibleux X, Beugnies F, Randriamasy S (2006) Martins’ algorithm revisited for multi-objective shortest path problems with a MaxMin cost function 4OR 4:47–59 Gendreau M, Laporte G, Semet F (1997) The covering tour problem. Oper Res 45(4): 568–576 Glover F, Laguna M (1997) Tabu Search. Kluwer Academic Publishers, Dordrecht, p 111 Gouveia L, Patrício P, de Sousa A (2008) Hop-constrained node survivable network design: an application to MPLS over WDM. Netw Spatial Econ 8(1): 3–21 Hansen P, Mladenović N. (1997) Variable neighborhood search. Comput Oper Res 24: 1097–1100 Hansen P, Mladenović N (2003) Variable neighbourhood search. In: Glover F, Kochenberger GA (eds) Handbook of metaheuristics, pp 145–158 Hodgson MJ, Laporte G, Semet F (1998) A covering tour model for planning mobile health care facilities in Suhum district, Ghana. J Reg Sci 38(4): 621–639 Kovács G, Spens KM (2007) Humanitarian logistics in disaster relief operations. Int J Phys Distrib Logist Manag 37(2): 99–114 Kovács G, Tatham P (2009) Responding to disruptions in the supply network–from dormant to action. J Bus Logist 30(2): 215–219 Lang S, Tiede D, Holbling D, Fureder P, Zeil P (2010) Earth observation (EO)-based ex post assessment of internally displaced person (IDP) camp evolution and population dynamics in Zam Zam, Darfur. Int J Remote Sens 31(21): 5709–5731 Matisziw TC, Murray AT (2009) Modeling s–t path availability to support disaster vulnerability assessment of network infrastructure. Comput Oper Res 36(1): 16–26 McLachlin R, Larson P, Khan S (2009) Not-for-profit supply chains in interrupted environments: the case of a faith-based humanitarian organisation. Manag Res News 32(11): 1050–1064 Nolz P, Doerner K, Gutjahr W, Hartl R (2009) A Bi-objective metaheuristic for disaster relief operation planning. In: Coello CA, Dhaenens C, Jourdan L (eds) Advances in multi-objective nature inspired computing. Springer, Berlin, pp 169–191 Özdamar L, Ediz E, Beste K (2004) Emergency logistics planning in natural disasters. Ann Oper Res 129: 217–245 Peduzzi P, Dao H, Herold C, Mouton F (2009) Assessing global exposure and vulnerability towards natural hazards: the disaster risk index. Natural Hazards Earth SystSci 9(4): 1149–1159 Reasenberg PA, Jones LM (1994) Earthquake aftershocks: update. Science 265(5176): 1251–1252 Soni S, Pirkul H (2002) Design of survivable networks with connectivity requirements. Telecommun Syst 20(1): 133–149 Sörensen K (2007) Distance measures based on the edit distance for permutation-type representations. J Heuristics 13(1): 35–47 Tiede D, Hoffmann C, Füreder P, Hölbling D, Lang S (2010) Automated damage assessment for rapid geospatial reporting—first experiences from the Haiti earthquake 2010. In: Car A, Griesebner G, Strobl J (eds) Geospatial Crossroads @ GI Forum’10. Proceedings of the Geoinformatics Forum Salzburg, pp 207–210 Van Wassenhove LN (2006) Humanitarian aid logistics: supply chain management in high gear. J Oper Res Soc 57(5): 475–489 Viswanath K, Peeta S (2003) The multicommodity maximal covering network design problem for planning critical routes for earthquake response. 82nd Annual meeting of the transportation research board Yi W, Özdamar L (2007) A dynamic logistics coordination model for evacuation and support in disaster response activities. Eur J Oper Res 179: 1177–1193 Zitzler E, Thiele L (1999) Multiple objective evolutionary algorithms: a comparative case study and the strength of the pareto approach. IEEE Trans Evolut Comput 3(4): 257–271 Zografos KG, Androutsopoulos KN (2008) A decision support system for integrated hazardous materials routing and emergency response decisions. Transp Res Part C: Emerg Technol 16(6): 684–703