Multivariate process capability evaluation of cloud manufacturing resource based on intuitionistic fuzzy set

Bi-Level Programming Model of Cloud Manufacturing Services Based on Extension Theory

“…Reference [26] presented dynamic update method of the QoS attribute vector by feedback control and selected services based on the preference weight and QoS attribute vector by technique for order preference by similarity to ideal solution (TOPSIS). According to the fuzzy quality theory, the dominance degree of intuitionistic fuzzy value is taken into account in decision-making; [27] proposed a method for resource service optimal selection based on multivariate process indicator and dominance degree of intuitionistic fuzzy value. From geo-perspective, Lartigau et al [28] adopted an improved artificial bee colony optimization for QoS to optimal select service compositions.…”

“…In order to analyze the advantages of extension evaluation in services evaluation, a comparative analysis is conducted with TOPSIS evaluation method [26], variable precision rough set method [25], and intuitionistic fuzzy evaluation method [27]. The results of other three methods are shown in Table 6.…”

“…The weights in this method are determined by the experience of all demanders, which ignores demanders' preferences, and only apply to those who have no experience at the beginning. Finally, compared with intuitionistic fuzzy methods [27], in intuitionistic fuzzy operations, the calculation will increase sharply with the increase of evaluation index, which is not suitable with the calculation for the big data. The proposed algorithm in this paper has a good theoretical basis, a small amount of calculation, and flexible parameter setting and can be adapted to different environments.…”

“…The benefits of service providers are as important as demander's in this experiment, w 1 =w 2 =0.5. Then, the single-objective programming model is established from formula (27) to formula (32). Solving the proposed model, the optimal results for both sides are output.…”

Ganging of Resources via Fuzzy Manhattan Distance Similarity with Priority Tasks Scheduling in Cloud Computing

“…Step-by-step instructions to choose the ideal assets series or assets combinations to finish the manufacturing task with a number of distributed subtasks was a key consideration in the investigation of cloud manufacturing. Cao et al [21] had developed a multivariate process capability indicator to assess the manufacturing process with the unwavering quality of information on cloud scheduling. As indicated by the fuzzy quality theory, the strength level of intuitionistic fuzzy esteem was considered in decision making while selecting the ideal asset chain.…”