Multi-criteria logistics modeling for military humanitarian assistance and disaster relief aerial delivery operations

被引:29
作者
Bastian, Nathaniel D. [1 ]
Griffin, Paul M. [2 ]
Spero, Eric [3 ]
Fulton, Lawrence V. [4 ]
机构
[1] Penn State Univ, Dept Ind & Mfg Engn, 355 Leonhard Bldg, University Pk, PA 16802 USA
[2] Georgia Inst Technol, Sch Ind & Syst Engn, 755 Ferst Dr, Atlanta, GA 30332 USA
[3] US Army, Res Lab, Vehicle Appl Res Div, 4603 Flare Loop, Aberdeen, MD 21005 USA
[4] Texas Tech Univ, Rawls Coll Business Adm, 703 Flint Ave, Lubbock, TX 79410 USA
基金
美国国家科学基金会;
关键词
Multiple criteria decision analysis; Stochastic optimization; Facility location; Humanitarian logistics; Supply chain engineering; Aerial delivery operations; OPTIMIZATION;
D O I
10.1007/s11590-015-0888-1
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Given that it is not always feasible to reach an affected area via land or sea within the first week following a natural disaster, aerial delivery provides the primary means to rapidly supply the affected population. Further, it is often the case that high density delivery of humanitarian aid supplies are taken over by non-friendly groups within the affected population. By using direct airdrop systems to deliver large quantities of individually wrapped food and water items, dispersion among the affected disaster relief population will occur more quickly. In this paper, we proffer a multiple criteria decision analysis (MCDA) framework to optimize the military humanitarian assistance/disaster relief (HA/DR) aerial delivery supply chain network. The model uses stochastic, mixed-integer, weighted goal programming to optimize network design, logistics costs, staging locations, procurement amounts, and inventory levels. The MCDA framework enables decision-makers to explore the trade-offs between military HA/DR aerial delivery supply chain efficiency and responsiveness, while optimizing across a wide range of real-world, probabilistic scenarios to account for the inherent uncertainty in the location of global humanitarian disasters as well as the amount of demand to be met.
引用
收藏
页码:921 / 953
页数:33
相关论文
共 38 条
[1]  
Akkihal A.R., 2006, INVENTORY PREPOSITIO
[2]  
[Anonymous], 2014, EM EV DIS DAT
[3]  
[Anonymous], 2013, WORLD FACTB 2013 14
[4]   Facility location in humanitarian relief [J].
Balcik, B. ;
Beamon, B. M. .
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS, 2008, 11 (02) :101-121
[5]   Coordination in humanitarian relief chains: Practices, challenges and opportunities [J].
Balcik, Burcu ;
Beamon, Benita M. ;
Krejci, Caroline C. ;
Muramatsu, Kyle M. ;
Ramirez, Magaly .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2010, 126 (01) :22-34
[6]   A Robust, Multi-criteria Modeling Approach for Optimizing Aeromedical Evacuation Asset Emplacement [J].
Bastian, Nathaniel D. .
JOURNAL OF DEFENSE MODELING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS, 2010, 7 (01) :5-23
[7]  
Beamon B. M., 2004, P INT C COMP IND ENG
[8]   Performance measurement in humanitarian relief chains [J].
Beamon, Benita M. ;
Balcik, Burcu .
INTERNATIONAL JOURNAL OF PUBLIC SECTOR MANAGEMENT, 2008, 21 (01) :4-+
[9]   A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty [J].
Bozorgi-Amiri, Ali ;
Jabalameli, M. S. ;
Al-e-Hashem, S. M. J. Mirzapour .
OR SPECTRUM, 2013, 35 (04) :905-933
[10]  
De la Torre LuisE, 2012, SOCIOECON PLANN SCI, V46, P88, DOI DOI 10.1016/J.SEPS.2011.06.001