A stochastic programming model for emergency supply planning considering transportation network mitigation and traffic congestion

Abstract How to conduct effective and efficient emergency supply planning is a challenging task. In this paper, we tackle a general emergency supply planning problem. The problem not only integrates the decisions of transportation network mitigation and emergency supply pre-positioning before disasters, but also considers post-disaster dynamic transportation planning with traffic congestion effects incorporated. We formulate this problem as a two-stage stochastic programming model, which aims to minimize the expected total cost related to various disaster mitigation, preparedness, and response decisions. A variant of the model is optimally solved by applying a generalized Benders decomposition algorithm, which significantly outperforms state-of-the-art global optimization solvers. Finally, a case study for a hurricane threat in the southeastern U.S. is conducted to demonstrate the advantages of our model and to illustrate insights on the optimal network mitigation and pre-positioning plan as well as the transportation plan. It is shown that considering traffic congestion effects and dynamic transportation plans brings about spatial and temporal flexibility for achieving better emergency supply plans.

[1]  S. Travis Waller,et al.  A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations , 2010, Comput. Aided Civ. Infrastructure Eng..

[2]  Hande Yaman,et al.  Compromising system and user interests in shelter location and evacuation planning , 2015 .

[3]  A. Apte,et al.  Stochastic Optimization for Natural Disaster Asset Prepositioning , 2010 .

[4]  Shaligram Pokharel,et al.  Optimization models in emergency logistics: A literature review , 2012 .

[5]  Antoine G. Hobeika,et al.  A LOCATION-ALLOCATION MODEL AND ALGORITHM FOR EVACUATION PLANNING UNDER HURRICANE/FLOOD CONDITIONS , 1991 .

[6]  Nilay Noyan,et al.  A chance-constrained two-stage stochastic programming model for humanitarian relief network design , 2018 .

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

[8]  Abbas Seifi,et al.  A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district , 2015 .

[9]  Xiaofeng Nie,et al.  A stochastic programming model for emergency supply planning considering traffic congestion , 2019, IISE Trans..

[10]  F. Sibel Salman,et al.  Pre-disaster investment decisions for strengthening a highway network , 2010, Comput. Oper. Res..

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

[12]  Lili Du,et al.  A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions , 2014 .

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

[14]  Changzheng Liu,et al.  Solving Stochastic Transportation Network Protection Problems Using the Progressive Hedging-based Method , 2010 .

[15]  D. Z. Wang,et al.  Global optimization method for network design problem with stochastic user equilibrium , 2015 .

[16]  S. Hallegatte,et al.  From A Rocky Road to Smooth Sailing , 2019 .

[17]  A. M. Geoffrion.  Generalized Benders decomposition , 1972 .

[18]  Mingzhe Li,et al.  A location-routing model for prepositioning and distributing emergency supplies , 2016 .

[19]  William Hoffman.  Avoiding logistics disasters , 2005 .

[20]  Alfredo Moreno,et al.  Stochastic network models for logistics planning in disaster relief , 2016, Eur. J. Oper. Res..

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

[22]  Rachel A. Davidson,et al.  Shelter location and transportation planning under hurricane conditions , 2012 .

[23]  F. Sibel Salman,et al.  Improving post-disaster road network accessibility by strengthening links against failures , 2018, Eur. J. Oper. Res..

[24]  Hai Yang,et al.  A global optimization method for continuous network design problems , 2012 .

[25]  Hai Yang,et al.  Global optimization methods for the discrete network design problem , 2013 .

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

[27]  Hai Yang,et al.  Models and algorithms for road network design: a review and some new developments , 1998 .

[28]  H. Lo,et al.  Global optimization method for mixed transportation network design problem: A mixed-integer linear programming approach , 2011 .

[29]  Hande Yaman,et al.  Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach , 2017, Transp. Sci..

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

[31]  Gina Galindo,et al.  Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies , 2013 .

[32]  Changzheng Liu,et al.  A two-stage stochastic programming model for transportation network protection , 2009, Comput. Oper. Res..

[33]  Elise Miller-Hooks,et al.  Measuring the performance of transportation infrastructure systems in disasters: a comprehensive review , 2015 .

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

[35]  Hong Kam Lo,et al.  Global Optimum of the Linearized Network Design Problem with Equilibrium Flows , 2010 .