دانلود رایگان مقاله انگلیسی فرآیند تحلیل شبکه فاز شهودی - IEEE 2018

Abstract

Since the Analytic network process (ANP) is much more flexible than the analytic hierarchy process (AHP) in handling the multiple criteria decision making (MCDM) problems in which the criteria or sub-criteria are interdependent, it has attracted many scholars’ attention and has been applied into many different areas. Given the powerfulness of intuitionistic fuzzy set in representing positive, negative and indeterminate information, this paper investigates the ANP framework for the MCDM problems in which all the pairwise comparison judgment information over the objects are represented by intuitionistic fuzzy numbers. We first justify the way to decompose the MCDM problem into a holarchy and network structure, based on which, the intuitionistic fuzzy preference relations (IFPRs) can be constructed through pairwise comparisons over the goals, criteria, clusters as well as the elements. Considering that not all the IFPRs are consistent, we then propose a new method to derive the priorities from the IFPRs no matter the IFPRs are consistent or not. After that, we address the way to construct the supermatrix for those interdependent elements. The complete algorithm of intuitionistic fuzzy ANP (IFANP) is given and illustrated by a flow chart. To show the applicability and efficiency of the IFANP, we implement the method to a case study concerning the brand management of the six golden flowers of Sichuan liquor. Some comparative analyses are given to clarify the advantages and invalidation of the IFANP.

VIII. CONCLUSION

In this paper, we have developed the range of ANP application in the form of IFVs. The IFV is benificial to the DMs especially when tackling the MCDM problems. The IFV could express the membership degree, non-membership degree and the hestiancy degree, which almost show the value that the DMs want to give. We have put forward the procedure of the IFANP, and developed a new priority determining method from the IFPR to spare us from the complicated calculation which results from the there-dimensional degrees of IFVs.

It should be noted that Zhu et al. [34] introduced the generalized analytic network process, which can deal with intervals characterized by all distributions and the interval values and mathematically equivalent to the IFV. However, the underlying foundations between IFS and IVFS are quite different. The IFS uses two different indicators to represent the membership degree and non-membership degree; while the IVFS can only be used to represent the membership degree with intervals. Since Atanassov developed the IFS in 1986, it attracts many scholars’ interests and fruitful achievements can be seen in references. This shows that IFS has very good practical application potientials. Thus, it is important to investigate the IFANP paradigm to build an integrated framework of IFAHP method.

In the future, more priority deriving methods will be done and we will adapt the IFANP to solve other MCDM problems, such as R&D project selection, SWOT anlaysis, logistics service provider selection, production planning, and so forth. Furthermore, other information representational forms may be used in the pairwise judgements to be calculated in the ANP, for example, the hesitant fuzzy linguistic analytical network process.