摘要
R&D project-selection plays a very important role in R&D management.Whetar or not a R&D project is selected scientifieally will spell its success or failure.Aa a decision making R&D project-selection is characttrized by multiple procedues,multiple conflicting and noncommensurate objectives,and these characteristics make a numer of traditional approaches invalid or inefficient.In this paper,information flow and feedforward neural network method in R&D project-selection are pmentedi Through theoretical analysis,illustrative examples and computational simulation,we show that the proposed approach is preferable to the traditonal ones in many aspects.
R&D project-selection plays a very important role in R&D management.Whetar or not a R&D project is selected scientifieally will spell its success or failure.Aa a decision making R&D project-selection is characttrized by multiple procedues,multiple conflicting and noncommensurate objectives,and these characteristics make a numer of traditional approaches invalid or inefficient.In this paper,information flow and feedforward neural network method in R&D project-selection are pmentedi Through theoretical analysis,illustrative examples and computational simulation,we show that the proposed approach is preferable to the traditonal ones in many aspects.
