After the December 2004 tsunami that devastated many coastal regions in some South Asian and Southeast Asian countries, and due to the logistics challenges faced in recent large-scale natural disasters such as an earthquake and a tsunami in Japan (March 2011) and earthquakes in Pakistan (October 2005) and China (May 2008), the importance of emergency logistics planning in Asian megacities has increased many fold. Although a vast body of operations research literature deals with the dynamic and stochastic nature of the business logistics, such literature about emergency logistics is limited. One of the main characteristics that differentiate emergency logistics from business logistics is the predominant presence of uncertainty in demand, supply, and transportation networks (i.e., travel times) (Sheu 2007). For example, actual demand of relief and evacuation is always revealed during the actual relief operation (dynamic demand)—even though a demand forecast is usually available beforehand based on some probabilistic models. Hence, a good practice in emergency logistics planning can be the use of dynamic demand models with some stochastic information on demand.