Grey Relational Analysis and Forecast of Demand for Scrap Steel.

Abstract - This paper chooses scrap steel as research object, firstly we use grey relational analysis between the present phase of steel industry in China and three phases of that in developed countries according to industrial lifecycle. Then we set up GM(l,l) power model, and build objective function of least average comparative error, solve the optimized solution of its whitenization equation by particle swarm optimization algorithm. At last, apply it to forecast the demand of scrap steel for the next several years in China. The forecasted result is consistent with fact, and the demand we forecast gives scientific evidence to the design of reverse logistics networks. [ABSTRACT FROM AUTHOR]