TY  - JOUR
AB  - Purpose– The purpose of this paper is to overcome the deficiency of the current GM(1,N) such as low‐prediction precision, extend the scope of GM(1,N) and provide an effective grey dynamic model GM(1,N) for the relationship of cost and variability.Design/methodology/approach– The relationship between two factors of variety and the cost of manufacturing system is studied on the basis of the variety reduction program theory. Based on the Grey system and the gradient algorithm, a Grey dynamic model GM(1,N) is proposed between cost and variety by optimizing the coefficient and background value of the model which is used to check validity for the relation of plasm‐yarn machine product and variety.Findings– The proposed Grey dynamic prediction model GM(1,N) for the relationship of cost and variability has high precision and easy‐to‐use.Research limitations/implications– A Grey model GM(1,N) for prediction is proposed.Practical implications– The proposed model should also have potential for multifactor system prediction in engineering.Originality/value– The deficiency of the current GM(1,N) is overcome, the scope of GM(1,N) is extended and the proposed Grey dynamic model GM(1,N) has high‐prediction precision.
VL  - 38
IS  - 3/4
SN  - 0368-492X
DO  - 10.1108/03684920910944137
UR  - https://doi.org/10.1108/03684920910944137
AU  - Youxin Luo
AU  - Xiao Wu
AU  - Min Li
AU  - Anhui Cai
ED  - Mian‐yun Chen
ED  - Yi Lin
ED  - Hejing Xiong
PY  - 2009
Y1  - 2009/01/01
TI  - Grey dynamic model GM(1,N) for the relationship of cost and variability
T2  - Kybernetes
PB  - Emerald Group Publishing Limited
SP  - 435
EP  - 440
Y2  - 2024/05/09
ER  -