Prepositioning Emergency Supplies to Support Disaster Relief : A Stochastic Programming Approach

This paper studies the strategic problem of designing emergency supply networks to support disaster relief over a planning horizon. This problem addresses decisions on the location and number of distribution centers needed, their capacity, and the quantity of each emergency item to keep in stock in time. To tackle the problem, a scenario based approach is proposed involving three phases: disasters scenario generation, design generation and design evaluation. Disasters are modeled as stochastic processes and a Monte Carlo procedure is derived to generate plausible catastrophic scenarios. Based on this detailed representation of disasters, a multi-phase modeling framework is proposed to design the emergency supply network. The two-stage stochastic programming formulation proposed is solved using a sample average approximation method. This scenario based solution approach is tested with a case inspired from realworld data to generate plausible scenarios, to produce a set of alternative designs and then to evaluate them on a set of performance measures in order to select the best design.

[1]  Gwo-Hshiung Tzeng,et al.  Multi-objective optimal planning for designing relief delivery systems , 2007 .

[2]  Lawrence V. Snyder,et al.  Facility location under uncertainty: a review , 2006 .

[3]  Philip C. Jones,et al.  Prepositioning supplies in preparation for disasters , 2011, Eur. J. Oper. Res..

[4]  Debarati Guha-Sapir,et al.  Annual Disaster Statistical Review 2009The numbers and trends , 2010 .

[5]  Anup Roop Akkihal,et al.  Inventory pre-positioning for humanitarian operations , 2006 .

[6]  Luk N. Van Wassenhove,et al.  Humanitarian aid logistics: supply chain management in high gear , 2006, J. Oper. Res. Soc..

[7]  Pinar Keskinocak,et al.  Pre-Positioning of Emergency Items for CARE International , 2011, Interfaces.

[8]  Soumia Ichoua,et al.  Relief Distribution Networks: Design and Operations , 2011 .

[9]  Mark S. Daskin,et al.  α-reliable p-minimax regret: a new model for strategic facility location modeling , 1997 .

[10]  N. C. Simpson,et al.  Fifty years of operational research and emergency response , 2009, J. Oper. Res. Soc..

[11]  Christos Douligeris,et al.  Optimal location and capacity of emergency cleanup equipment for oil spill response , 1997 .

[12]  Mei-Shiang Chang,et al.  A scenario planning approach for the flood emergency logistics preparation problem under uncertainty , 2007 .

[13]  Benita M. Beamon,et al.  Facility location in humanitarian relief , 2008 .

[14]  H. Kunreuther,et al.  Catastrophe modeling : a new approach to managing risk , 2013 .

[15]  Mark A. Turnquist,et al.  Pre-positioning of emergency supplies for disaster response , 2010 .

[16]  Maged Dessouky,et al.  Capacitated Facility Location With Distance-Dependent Coverage Under Demand Uncertainty , 2014 .

[17]  Alexander Shapiro,et al.  Stochastic programming approach to optimization under uncertainty , 2007, Math. Program..

[18]  Alain Martel,et al.  Designing global supply networks for conflict or disaster support: the case of the Canadian Armed Forces , 2013, J. Oper. Res. Soc..

[19]  Emmett J. Lodree,et al.  An insurance risk management framework for disaster relief and supply chain disruption inventory planning , 2008, J. Oper. Res. Soc..

[20]  F. Sibel Salman,et al.  Locating disaster response facilities in Istanbul , 2011, J. Oper. Res. Soc..

[21]  Satish V. Ukkusuri,et al.  Location Routing Approach for the Humanitarian Prepositioning Problem , 2008 .

[22]  Mark S. Daskin,et al.  Network and Discrete Location: Models, Algorithms and Applications , 1995 .

[23]  Maged Dessouky,et al.  A modeling framework for facility location of medical services for large-scale emergencies , 2007 .

[24]  Zelda B. Zabinsky,et al.  Stochastic optimization of medical supply location and distribution in disaster management , 2010 .

[25]  Karl F. Doerner,et al.  Risk approaches for delivering disaster relief supplies , 2011, OR Spectr..

[26]  Alain Martel,et al.  Scenario-based Supply Chain Network risk modeling , 2012, Eur. J. Oper. Res..

[27]  Mark A. Turnquist,et al.  Pre-positioning planning for emergency response with service quality constraints , 2011, OR Spectr..

[28]  Nezih Altay,et al.  OR/MS research in disaster operations management , 2006, Eur. J. Oper. Res..

[29]  L. V. Van Wassenhove.  Humanitarian aid logistics: supply chain management in high gear , 2006 .

[30]  Yacov Y. Haimes,et al.  Risk modeling, assessment, and management , 1998 .

[31]  Antonio Alonso Ayuso,et al.  Introduction to Stochastic Programming , 2009 .

[32]  Philip J. Schneider,et al.  Natural Hazards—The Multihazard Approach , 2006 .

[33]  Mariel S. Lavieri,et al.  A Florida County Locates Disaster Recovery Centers , 2005, Interfaces.

[34]  Emmett J. Lodree,et al.  Supply chain planning for hurricane response with wind speed information updates , 2009, Comput. Oper. Res..

[35]  Mark A. Turnquist,et al.  Pre-positioning of Emergency Supplies for Disaster Response , 2006, 2006 IEEE International Symposium on Technology and Society.

[36]  Mark A. Turnquist,et al.  Pre-positioning and dynamic delivery planning for short-term response following a natural disaster , 2012 .

[37]  Mark S. Daskin,et al.  Planning for Disruptions in Supply Chain Networks , 2006 .

[38]  S. Raghavan,et al.  The Mobile Facility Routing Problem , 2011, Transp. Sci..