Open Science Research Excellence
%0 Journal Article
%A Yousef Abu Nahleh and  Arun Kumar and  Fugen Daver and  Reham Al-Hindawi
%D 2014 
%J  International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 90, 2014
%T Decision Tree Modeling in Emergency Logistics Planning
%V 90
%X Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability of disaster for each country in the world by using decision tree modeling. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.

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