Optimal selection of manufacturing services in cloud manufacturing: A novel hybrid MCDM approach based on rough ANP and rough TOPSIS

摘要

In order to achieve optimal selection of manufacturing services in cloud manufacturing environment, this paper proposed a novel hybrid MCDM approach integrated Rough Analytic Network Process (rough ANP) and Rough Technique for Order of Preference by Similarity to Ideal Solution (rough TOPSIS). In the first step, the novel evaluation method based on rough-ANP is proposed to determine weight of each indicator. In the second step, the decision-making system based on rough-TOPSIS is developed to compare and rank alternatives. At the same time, in group decision-making process, the concepts of rough number and rough boundary are introduced to express more integrated information. The novel approach makes use of the strength of rough set theory in handling vagueness and uncertainty, the superiority of Analytic Network Process (ANP) in non-independent hierarchy evaluation and the advantage of TOPSIS in multiple-objective decision analysis. Finally, a case study is presented to demonstrate the practicability and validity of the novel approach.