A macro-location model of Logistics node and its application

The paper presents a novel Uncertain Cost-Revenue (UCR) model based on Fuzzy Multiple Attribute Hierarchical Macro-Location model (FMAHML) of Logistics node, which uses “bounded rationality”, “bounded memory” and “group decision making” methods with multi-resolution technology. It is integrated with multiple attribute decision making, fuzzy decision making, Analytic Hierarchy Process (AHP) and Delphi method. UCR, which considers uncertainties and risks of factors, is presented firstly. Cost and revenue are both considered and transformed into utilities by alternative functions in UCR model. A unified evaluation criterion is established between cost and revenue. Additionally, the paper also proves the convergence of UCR model and shows main application steps of UCR model. Finally, the paper shows how to use it to solve real problems by a case study. So it has a high practical value.