Relief Demand Forecasting in Emergency Logistics Based on Tolerance Model

Various disasters with serious results are reported and happen around our lives. Most of them are unconventional contingency events that are difficult to be detected and discriminated. Emergency management is an important activity dealing with the contingent events. For the uncertainty, imperfect, stochastic, fuzzy and disturbed environments and the unrecognized characteristics of the events, it is hard to make the urgent decision for relief demands in the context of emergency management. Inspired by the higher efficiency and special structure of immune system dealing with the pathogens, and the tolerance mechanisms dealing with incentives, a tolerance model based approach is proposed to forecast the emergency demands for protect disaster node. The concepts, models and algorithms are studied.