Power restoration in emergency situations
CIE '96 Proceedings of the 19th international conference on Computers and industrial engineering
The Censored Newsvendor and the Optimal Acquisition of Information
Operations Research
Quantity flexibility contracts under Bayesian updating
Computers and Operations Research
Bayesian solution to pricing and inventory control under unknown demand distribution
Operations Research Letters
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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.