Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment

2022 ◽  
Vol 175 ◽  
pp. 121414
Author(s):  
Shouzhen Zeng ◽  
Na Zhang ◽  
Chonghui Zhang ◽  
Weihua Su ◽  
Llopis-Albert Carlos
Author(s):  
Ahmed ElSayed ◽  
Elif Kongar ◽  
Surendra M. Gupta

<p>This paper presents a newly developed fuzzy linear physical programming (FLPP) model that allows the decision maker to introduce his/her preferences for multiple criteria decision making in a fuzzy environment. The major contribution of this research is to generalize the current models by accommodating an environment that is conducive to fuzzy problem solving. An example is used to evaluate, compare and discuss the results of the proposed model.</p>


2016 ◽  
Vol 15 (05) ◽  
pp. 1157-1179 ◽  
Author(s):  
N. Thillaigovindan ◽  
S. Anita Shanthi ◽  
J. Vadivel Naidu

This paper considers a multiple criteria decision-making (MCDM) problem under risk in fuzzy environment in its general form. There are m alternatives which need to be ranked on the basis of a set of n criteria. The alternatives and the criteria are evaluated based on a set of l characteristics. The entire data is presented in the form of interval valued intuitionistic fuzzy soft set of root type. In addition each criterion is assigned a subjective criterion weight based on expert’s evaluation and each characteristic is assigned a probability weight on the basis of decision maker’s knowlege and understanding of the importance of the characteristic. This problem may be called as a MCDM problem under risk in fuzzy environment in its general form. A method for ranking the alternatives using the new score functions, prospect theory and method of determining the optimum criteria weights is explained. An algorithm is developed for this purpose and its working illustrated with a suitable example.


Author(s):  
Alessandro Di Stefano ◽  
Marialisa Scatà ◽  
Aurelio La Corte ◽  
Evelina Giacchi

Complexity and dynamics characterize a social network and its processes. Social network analysis and graph theory could be used to describe and explore the connectedness among the different entities. Network dynamics further increases the complexity, as each entity with its personal knowledge, cognitive and reasoning capabilities, thinks, decides and acts in a social network, characterized by the heterogeneity of nodes and ties among them. Social network analysis becomes critical to the decision-making process, where a network node will consider both its personal knowledge and the influences received from its neighbors. Network dynamics and the node's context-awareness affect the relationships among criteria, modifying their ranking in a multiple criteria decision-making process, and hence the decision itself. Thus, the main aim has been to model the decision-making process within a social network, considering both context-awareness and network dynamics. Moreover, we have introduced a process of knowledge-transfer, where the criteria are represented by the knowledge-related values.


2020 ◽  
Vol 31 (1) ◽  
pp. 61-71 ◽  
Author(s):  
Hongrun Zhang ◽  
Huchang Liao ◽  
Xingli Wu ◽  
Edmundas Kazimieras Zavadskas ◽  
Abdullah Al-Barakati

Abstract   The number of products based on internet financial platform has increased dramatically, but due to the lack of effective regulatory system and the information barrier of investors, product returns have been greatly discounted and investment risks have been greatly increased. How to select high-quality products in internet finance based on several indicators is an important multiple criteria decision making problem. In this regard, this study develops a Pythagorean fuzzy double normalization-based multiple aggregation (PF-DNMA) method to solve the problem of selecting internet financial products. Firstly, the key factors for evaluating internet financial products are identified. Observing that the Pythagorean fuzzy set is an effective tool to express evaluation information, we then extend the original multiple criteria decision making method named the double normalization-based multiple aggregation method to Pythagorean fuzzy environment. The PF-DNMA method is characterized by two normalization techniques and three aggregation tools, and thus is effective and robust in solving multiple criteria decision making problems. We deal with an internet financial investment problem by the PL-DNMA method and provide some comparative analyses with the Pythagorean fuzzy TOPSIS and VIKOR methods to illustrate the effectiveness of the proposed method.


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