A secure and efficient inventory management system for disasters

Over the last three decades, disasters worldwide claimed more than 3 million lives and adversely affected the lives of at least 1 billion people (Noji, 1997). Regarding the threats posed by these disasters, emergency disaster management has emerged as a vital tool to reduce the harm and alleviate the suffering these disasters can cause to their victims. A significant task of planners involved in emergency disaster management is planning for and satisfying the vital needs of the people located in emergency shelters such as the Superdome in New Orleans. This thesis proposes a novel and comprehensive framework for the development of a humanitarian emergency inventory management system based on the real-time tracking of emergency supplies and demands through the integration of emerging technologies such as Radio Frequency Identification Devices (RFID) for commodity tracking and logistics. The novelty of this thesis is that, for the first time in the emergency inventory management field, the proposed approach combines an offline planning strategy with online control techniques in a unified framework. Within this framework, the offline planning problem is solved by the stochastic humanitarian inventory management approach, whereas the online modeling strategies include the application of neural network-based functional approximation, simultaneous perturbation stochastic approximation (SPSA), and continuous time model predictive control (CMPC) techniques. Unlike previous studies, the flexibility of the proposed inventory management and control model allows the application of the developed mathematical model to extreme events making online real-time tracking possible. Realistic case studies built using information available from past disasters are used to examine the differences in inventory strategies for different types of disasters based on the impact area and duration of the extreme event. The proposed methodology is also capable of representing and understanding real-life cases where uncertainty and limitations on the inventory levels and flow of supplies can be modeled by introducing different levels of stochasticity and real-life constraints. The overall findings of this thesis have pointed out that the proposed integrated framework can be efficiently used for emergency inventory planning and inventory control during disaster relief operations without ignoring the real-world uncertainties, fluctuations, and constraints of disaster conditions.Ph. D.Includes bibliographical referencesIncludes vitaby Eren Erman Ozguve