مقاله انگلیسی رایگان در مورد فرآیند تحلیل شبکه فاز شهودی – IEEE 2018

ANALYTIC network process (ANP), firstly brought out by Saaty in 1996 [1], allows one to include all the factors and criteria that have impacts on making a best decision. It is of great use in assisting the mind to organize its thoughts and experiences and to elicit judgments recorded in memory and qualify them in the form of priorities. It allows the decision makers (DMs) to represent diverse opinions after discussion and debate. The ANP, as a generalized model of the analytic hierarchy process (AHP) [2], not only can solve the AHP problems, but also can tackle interdependent relationships within multiple criteria decision making (MCDM) problems by replacing hierarchies with networks. It is based on deriving ratio scale measurements and can be used to allocate resources according to their ratio-scale priorities. It provides a way to the input judgments and measurements to derive ratio scale priorities for the distribution of influences among the factors and groups of factors in the decision making problem. The steps of ANP involve the following steps: ① constructing control hierarchy and network and identifying feedbacks or dependences among the elements and clusters, ② constructing the pairwise comparison matrices regarding to the elements and clusters, ③ deriving local priorities and constructing unweighted supermatrix with local priorities, ④ adjusting the unweighted supermatrix to the weighted supermatrix (also called as column stochastic matrix), ⑤ limiting the weighted supermatrix by raising it to an arbitrarily large power and calculating the limit priorities from it , and ⑥ deriving the final priorities of the alternatives. Although the traditional ANP is widely used in management science and operations research, we shall not ignore its drawback: the DMs cannot guarantee that the judgements valued by them are exact and crisp. During the pairwise comparison procedure, the DMs usually are required to give the value of the preference relation by crisp numbers based on the knowledge and experience they owned. However, only by the crisp numbers cannot express the DMs’ uncertainty on the preference relation. If the experts cannot clearly comprehend the problem, they are unwilling to give their judgements by crisp values, and then we cannot successfully solve the problem. In order to overcome this shortcoming of ANP, Mikhailov and Singh [3] made enormous strides in the direction of fuzzy ANP (FANP) and its applications in MCDM. So far, the FANP have been applied in many areas, such as evaluating region agricultural drought risks [4], selecting container ports [5], selecting social media platform [6], choosing supplier [7], evaluating ship maneuverability [8], and determining the importance of hospital information system adoption factors [9].