Supply chain planning for hurricane response with wind speed information updates

被引:48
作者
Lodree, Emmett J., Jr. [1 ]
Taskin, Selda [1 ]
机构
[1] Auburn Univ, Dept Ind & Syst Engn, Auburn, AL 36849 USA
关键词
Inventory control; Disaster recovery planning; Disaster relief planning; Hurricane logistics planning; Optimal stopping problem; Bayesian updating; INVENTORY CONTROL; ORDERING POLICY; LOGISTICS; MODELS;
D O I
10.1016/j.cor.2007.09.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper introduces a stochastic inventory control problem that is relevant to proactive disaster recovery planning as it relates to preparing for potential hurricane activity. In particular, we consider a manufacturing or retail organization who experiences demand surge for items such as flashlights, batteries, and gas-powered generators, where the magnitude of demand surge is influenced by various characteristics of an ensuing storm. The planning horizon begins during the initial stages of storm development, when a particular tropical depression or disturbance is first observed, and ends when the storm dissipates. Since hurricane characteristics can be predicted with more accuracy during the later stages of the planning horizon relative to the earlier stages, the inventory control problem is formulated as an optimal stopping problem with Bayesian updates, where the updates are based on hurricane predictions. A dynamic programming algorithm is described to solve the problem, and several examples involving real hurricane wind speed data are presented to illustrate the methodology. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2 / 15
页数:14
相关论文
共 41 条
[1]   OR/MS research in disaster operations management [J].
Altay, Nezih ;
Green, Walter G., III .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 175 (01) :475-493
[2]   Inventory control of spare parts using a Bayesian approach: A case study [J].
Aronis, KP ;
Magou, L ;
Dekker, R ;
Tagaras, G .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 154 (03) :730-739
[3]   BAYES SOLUTION TO DYNAMIC INVENTORY MODELS UNDER UNKNOWN DEMAND DISTRIBUTION [J].
AZOURY, KS .
MANAGEMENT SCIENCE, 1985, 31 (09) :1150-1160
[4]   A COMPARISON OF THE OPTIMAL ORDERING LEVELS OF BAYESIAN AND NON-BAYESIAN INVENTORY MODELS [J].
AZOURY, KS ;
MILLER, BL .
MANAGEMENT SCIENCE, 1984, 30 (08) :993-1003
[5]   An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations [J].
Barbarosoglu, G ;
Özdamar, L ;
Çevik, A .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2002, 140 (01) :118-133
[6]  
Beamon B.M., 2006, INT J LOGIST-RES APP, V9, P1, DOI DOI 10.1080/13675560500453667
[7]  
Berger JO, 1985, Statistical decision theory, foundation, concepts and method
[8]  
Bryson KM, 2002, EUR J OPER RES, V141, P679, DOI 10.1016/S0377-2217(01)00275-2
[9]   Quick response policy with Bayesian information updates [J].
Choi, TM ;
Li, D ;
Yan, HM .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 170 (03) :788-808
[10]   Optimal single ordering policy with multiple delivery modes and Bayesian information updates [J].
Choi, TM ;
Li, D ;
Yan, HM .
COMPUTERS & OPERATIONS RESEARCH, 2004, 31 (12) :1965-1984