Demand Forecasting of Emergency Resource in Humanitarian Supply Chain
In the last decades, increasing in human and natural disaster occurrence, had very irreparable effects on human life.
In order to relieve the consequences of disasters, improving in accuracy and reliability of the demand forecasting system can be
a suitable solution because the demand prediction on emergency resources is the premise and basis of optimal allocation of
emergency resources. Nowadays, there are only few researches in this area in Iran and abroad. For this reason, the paper aims
at the characteristics of emergency resource demand forecasting in the humanitarian supply chain and presents a method for
emergency resource demand prediction using case-based reasoning (CBR). CBR is a recent approach to problem solving and
learning that has got a lot of attention over the last few years. In the proposed model, despite a few data, the estimate error is
very low, that implies on high accuracy of the model. This prediction method provides a method and model support for the
emergency resources allocation decision-making system to be constructed in future.
Index Terms - Humanitarian Supply Chain, Emergency Resource, Case-based Reasoning, Demand Forecasting.