Supply chain planning for hurricane response with information updates
Type of DegreeDissertation
Industrial and Systems Engineering
MetadataShow full item record
Planning inventories of supplies for the hurricane season can be challenging. For instance, in 2004, manufacturing and retail firms experienced stock outs because they were not prepared for responding to the demand caused by several hurricanes that swept through the state of Florida in the southeastern United States. In 2005, these firms again experienced shortages due to the extreme demand surge caused by Hurricane Katrina. These experiences motivated firms to be pro-active and more aggressive in their approach to stocking hurricane supplies in 2006, resulting in large amounts of excess inventory because of an inactive hurricane season. While there are many issues, such as evacuation decisions and cooperation among government agencies that need to be addressed in terms of developing effective plans for responding to disastrous hurricanes, this research investigates stochastic production/inventory control problems that are relevant to planning for potential disaster relief activities associated with hurricane events. In particular, this study considers supply chain organizations who experience demand surge for items such as flashlights, batteries, and gas-powered generators, where the magnitude of the demand surge is influenced by various characteristics of a hurricane season and/or a specific hurricane. These organizations are faced with challenging procurement and production decisions since the hurricane logistics planning process is complicated by the uncertainties associated with the number of hurricanes that will occur during a hurricane season, hurricane intensities, and locations affected during the season. This study aims to assist major corporations to quickly and cost effectively respond to demand surges caused by hurricanes. In this dissertation, two different types of stochastic inventory models are introduced to determine the appropriate hurricane stocking levels for these organizations. The first two models address a hurricane stocking problem that is relevant to disaster recovery planning. In this context, the disaster recovery plan requires to determine optimal ordering/production policies for supply chain organizations for whom, the magnitude of the demand surge is influenced by various characteristics of an observed storm during the hurricane season. The third model introduces a multi period hurricane inventory control problem that allows the managers to adjust inventory decisions during the pre-season periods as demand realizes to reserve for the hurricane season demand. The model enables decision makers (DMs) to determine the optimal level of reserved hurricane stock while satisfying the demand associated with the pre-season periods. Finally, the work accomplished for each chapter of this dissertation is summarized with their relevance and usefulness, and possible extensions of this research and future study are proposed.