Supplier Selection Model Based on D Numbers and Transformation Function

Abstract

Selecting reasonable suppliers can effectively improve the efficiency of enterprise supply chain management. Among them, expert evaluation is an important part of supplier selection problem, but the uncertainty, fuzziness and incompleteness of expert opinions make supplier selection problem difficult to solve. In order to systematically and effectively solve the uncertainty, ambiguity and incompleteness in supplier selection problem, this paper presents a new supplier selection method based on D numbers and transformation function. First, fuzzy preference relation is generated based on the decision matrix of pairwise comparisons given by experts. D numbers which can effectively deal with uncertain information extend fuzzy preference relation (D matrix). Second, the D matrix is converted into a crisp matrix form based on the integration representation of D numbers according to different situations whether or not the information in D matrix is complete. Third, the crisp matrix is converted into judgement matrix by using the transformation functions. Finally, analytic hierarchy process (AHP) method is applied based on the judgment matrix to give a priority weights for decision making. Three numerical examples and application of the supplier selection are used to show the feasibility and effectiveness of the proposed method.

Optimizing Enterprise Marketing Project Portfolios Using Fuzzy Ant Colony Optimization

“…Common optimization methods include greedy algorithms, dynamic programming, genetic algorithms, simulated annealing algorithms, ACO algorithms, etc. [22,23,24]. The ACO algorithm is adopted in this study to optimize the enterprise marketing project portfolio.…”

An Intelligent Fuzzy MCDM Model Based on D and Z Numbers for Paver Selection: IMF D-SWARA—Fuzzy ARAS-Z Model

“…IMF SWARA is more recent, and it has already been applied in various studies [26][27][28]. The SWARA method [29] in combination with D numbers [30] as already defined was applied to determine the weights of the criteria for the whole project of evaluation and selection of pavers for all road categories. The detailed IMF D-SWARA algorithm is shown in the paper [22], and the weights are shown further in the paper.…”