Search

The stock investment selection could be deemed as a classic multiple attribute group decision making (MAGDM) problem involving multiple conflicts and interleaved qualitative and quantitative attributes. Spherical fuzzy sets (SFSs) can excavate the potential vagueness and intricacy in MAGDM more effectively and deeply. This article we propose an integrated decision support system (IDSS) based on SFSs, prospect theory (PT), distance from average solution (EDAS) method and the MEthod based on the Removal Effects of Criteria (MEREC). The proposed IDSS, called SF-PT-EDAS-MEREC model, uses SFSs to describe the uncertain and obscure assessment information of DMs. The combination of PT and EDAS (PT-EDAS) method adequately captures DMs’ psychological behavior characteristics to execute more reasonable alternative evaluation. The MEREC is utilized to efficaciously obtain unknown attribute weights. In addition, this paper also presents a novel score function to compare spherical fuzzy numbers (SFNs) more directly and efficiently. Eventually, in order to illustrate the practicability of the proposed IDSS, two numerical examples of stock investment selection are employed to achieve this. Meanwhile, the comparative study with existing approach further demonstrates the effectiveness and superiority of SF-PT-EDAS-MEREC model.

Choosing the optimal network security service provider (NSSP) is a very important part of enterprise management decision. And the choice of NSSP is a typical multiple attribute group decision making (MAGDM) issue. In order to provide a better decision method for MAGDM problems, this paper integrates the TODIM method and the probabilistic uncertainty linguistic term set (PULTS), so as to propose the probabilistic uncertain linguistic TODIM model based on the prospect theory (PT-PUL-TODIM). The model combines the advantages of the prospect theory and TODIM method. In the end, a case study concerning NSSP selection problem is given to demonstrate the merits of the developed methods. First published online 31 March 2022

The stock investment selection could be deemed as a classic multiple attribute group decision making (MAGDM) problem involving multiple conflicts and interleaved qualitative and quantitative attributes. Spherical fuzzy sets (SFSs) can excavate the potential vagueness and intricacy in MAGDM more effectively and deeply. This article we propose an integrated decision support system (IDSS) based on SFSs, prospect theory (PT), distance from average solution (EDAS) method and the MEthod based on the Removal Effects of Criteria (MEREC). The proposed IDSS, called SF-PT-EDAS-MEREC model, uses SFSs to describe the uncertain and obscure assessment information of DMs. The combination of PT and EDAS (PT-EDAS) method adequately captures DMs' psychological behavior characteristics to execute more reasonable alternative evaluation. The MEREC is utilized to efficaciously obtain unknown attribute weights. In addition, this paper also presents a novel score function to compare spherical fuzzy numbers (SFNs) more directly and efficiently. Eventually, in order to illustrate the practicability of the proposed IDSS, two numerical examples of stock investment selection are employed to achieve this. Meanwhile, the comparative study with existing approach further demonstrates the effectiveness and superiority of SF-PT-EDAS-MEREC model. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide an efficient multiple attribute group decision making (MAGDM) method to better serve the decision-makers (DMs), considering the real psychological state and preferences of the DMs when facing different risks. In real life, MAGDM is a very complex and uncertain problem, which needs to be considered from many aspects. In view of this, the intuitionistic fuzzy TOPSIS method on the basis of cumulative prospect theory (IF-CPT-TOPSIS) is proposed in this paper, which can effectively solve the above problems, cater to the expectations of DMs, and make the decision results more objective and more reliable. The originality of this paper comes from three aspects. First, the new score function is combined with CRITIC method to calculate the weight of attributes, which eliminates the influence of Subjective preference of DMs and makes the primary information more reasonable. Furthermore, the use of the new score function can effectively avoid the exception conditions in the IFS problems. Secondly, applying the distance measurement formula of IFSs to determine the degree of approaching the ideal solution, so that the decision model can reflect the environmental changes more quickly. Thirdly, calculate the relative profit loss ratio of each scheme. Hence, each scheme is ranked and the optimal one is selected. Finally, in order to demonstrate the effectiveness of the model, a specific example is given and comparative analysis with the existing methods. The results show that the improved IF-CPT-TOPSIS method is useful and can be widely adapted for complex MAGDM problems. [ABSTRACT FROM AUTHOR]

With the rapid development of 3D printing technology, 3D printers are manufactured based on the principle of 3D printing technology are more and more widely used in the manufacturing industry. Choosing high quality 3D printers for industrial production is of great significance to the economic growth of enterprises. In fact, it is difficult to select the most optimal 3D printers under a single and simple standard. Therefore, this paper establishes the probabilistic double hierarchy linguistic EDAS (PDHL-EDAS) method for the multiple attribute group decision making (MAGDM). Then the CRITIC model is introduced to derive objective weight and the cumulative prospect theory is leaded into obtain the cumulative weight of PDHLTS. In addition, what's more, the PDHL-EDAS method is built and applied to the choice of high-quality 3D printer. Finally, compared with the available MAGDM methods under PDHLTS, the built method is proved to be scientific and effective. [ABSTRACT FROM AUTHOR]