In this research, motivated by the 2004 Asian Tsunami, we focus on a large-scale supply network problem during a disaster, known as humanitarian logistics or supply disruption. This is an emerging research domain gaining recent attention from several research communities. While several works exist in the pre-disaster operations, there is a clear need for research in post-disaster operations. Thus, several issues arise during a post-disaster, such as relief supply distribution and network restoration, are integrated and studied through Operations Research techniques, inclusive of multiple-criteria programming, goal programming, metaheuristics, etc. The poster shows the Multiple-Objective Integrated Response and Recovery (MOIRR) model, which provides an equity- or fairness-based solution for constrained capacity, budget, and resource problems in post-disaster logistics management. Further, a designed experiment for this NP-hard problem is conducted to analyze important aspects of the integrated problem for both small- and large-sized networks: full vs. partial restoration and pooled vs. separate budgeting approaches. Finally, the model is applied to a Hazus-generated regional case study in South Carolina (SC) based on an earthquake scenario and efficient Pareto frontiers are generated to understand the trade-off between the objectives of interest.
Ransikarbum, Kasin and Mason, Scott J., "Multiple-Objective Analysis of Integrated Relief Distribution and Network Restoration in Post-Disaster Humanitarian Logistics - Hazus based South Carolina (SC) Case Study" (2015). Graduate Research and Discovery Symposium (GRADS). 162.