Effectiveness Evaluation Method of Constellation Satellite Communication System with Acceptable Consistency and Consensus Under Probability Hesitant Intuitionistic Fuzzy Preference Relationship

System effectiveness evaluation is an important part of constellation satellite communication system research, with applications in project verification and optimization as well as tactical and technical measurement argumentation. This paper presents a systematic and comprehensive effectiveness evaluation method for a constellation satellite communication system under a probabilistic hesitant intuitionistic fuzzy preference relationship (PHIFPR), aiming to better address the fuzziness and uncertainty in effectiveness evaluation. First, a proposed definition of PHIFPR describes the hesitancy of evaluators, provides hesitancy distribution information, and depicts the worst negative information and risk preferences in effectiveness evaluation. Then, we deduce the approximate consistency index of PHIFPR and establish a mathematical programming model to increase individual consistency when the approximate consistency index does not reach a predetermined level. In the sequel, a proposed group consensus index uses the PHIFPR-based Hausdorff distance to measure the closeness between evaluators' judgements. Afterwards, a consistency and consensus improvement model is designed to retain the original opinions of evaluators to make the consistency and consensus of PHIFPRs acceptable. Moreover, a goal programming model is established to gain the reliable scheme priority weights by regarding the approximate consistency condition of a PHIFPR as a fuzzy constraint. Finally, an experimental example is offered to highlight the practicability and feasibility of the proposed method, and some comparative analyses with other methods offer insights into the designed method.

Priority Weights for Predicting the Success of Hotel Sustainable Business Models

This study proposes the use of consistent fuzzy preference relations to evaluate the structure of hotel sustainable business model (HSBM) dimensions and the corresponding hierarchy of evaluation indicators, and predict the overall probability of success. As fuzzy preference relations require, a group of hotel professionals in Taiwan was asked to process pairwise comparisons using linguistic variables to determine the weights of dimensions and indicators. According to the results, finances were found to be the most important dimension, followed by human capital. The number of local cultural events in the hotel was identified as the most important indicator. The predictive values revealed the possibility for successful HSBM implementation, shedding light on the vision of sustainability for the hotel industry. The results of the present study contribute to the literature on sustainability by determining the importance and weights of dimensions and indicators for hotel business models, providing an example of the use of this strategic tool in generating and modifying sustainable business models for the hotel industry.

To select suitable supplier for complex equipment military-civilian collaborative design based on fuzzy preference information that from matching perspective

Combine complex equipment collaborative development in military-civilian integration context not only fulfils actual development requirement, but also beneficial to the national economy. Design procedure as first stage of complex equipment military-civilian collaborative development process, select suitable design supplier is significant to whole development process of complex equipment. In order to select suitable design supplier for complex equipment, two aspects done in this paper. One is comprehensive analysis of evaluated influencing factors that affect complex equipment military-civilian collaborative design process, corresponding evaluation indicator constructed and a combination of grey correlation, entropy, DEMATEL (Decision-making Trial and Evaluation Laboratory) and VIKOR analysis theory to obtain grey entropy-DEMATEL-VIKOR, then the combined method is utilized to acquire matching attributes for followed research content. Meanwhile, satisfaction degree for matching side obtained with the help of information aggregation based on power generalized Heronian mean which on the basis of fuzzy preference information. Then, through constructed matching model, suitable design supplier obtained. Finally, a corresponding illustrative example given.

A novel group decision making method for interval-valued pythagorean fuzzy preference relations

Interval-valued Pythagorean fuzzy preference relation (IVPFPR) plays an important role in representing the complex and uncertain information. The application of IVPFPRs gives better solutions in group decision making (GDM). In this paper, we investigate a new method to solve GDM problems with IVPFPRs. Firstly, novel multiplicative consistency and consensus measures are proposed. Subsequently, the procedure for improving consistency and consensus levels are put forward to ensure that every individual IVPFPR is of acceptable multiplicative consistency and consensus simultaneously. In the context of minimizing the deviations between the individual and collective IVPFPRs, the objective experts’ weights are decided according to the optimization model and the aggregated IVPFPR is derived. Afterwards, a programming model is built to derive the normalized Pythagorean fuzzy priority weights, then the priority weights of alternatives are identified as well. An algorithm for GDM method with IVPFPRs is completed. Finally, an example is cited and comparative analyses with previous approaches are conducted to illustrate the applicability and effectiveness of the proposed method.

Evaluation of the product quality of the online shopping platform using t-spherical fuzzy preference relations

As a generalization of Pythagorean fuzzy sets and picture fuzzy sets, spherical fuzzy sets provide decision makers more flexible space in expressing their opinions. Preference relations have received widespread acceptance as an efficient tool in representing decision makers’ preference over alternatives in the decision-making process. In this paper, some new preference relations are investigated based on the spherical fuzzy sets. Firstly, the deficiency of the existing operating laws is elaborated in detail and three cases are described to identify the accuracy of the proposed operating laws in the context of t-spherical fuzzy environment. Also, a novel score function is proposed to obtain the consistent value in ranking of the alternatives. The backbone of this research, t-spherical fuzzy preference relation, consistent t-spherical fuzzy preference relations, incomplete t-spherical fuzzy preference relations, consistent incomplete t-spherical fuzzy preference relations, and acceptable incomplete t-spherical fuzzy preference relations are established. Additionally, some ranking and selection algorithms are established using the proposed novel score function and preference relations to tackle the uncertainty in real-life decision-making problems. Finally, evaluation of the product quality of the online shopping platform problem is demonstrated to show the applicability and reliability of proposed technique.