Interval type-2 fuzzy programming method for risky multicriteria decision-making with heterogeneous relationship

A model for emergency supply management under extended EDAS method and spherical hesitant fuzzy soft aggregation information

Due to the frequent occurrence of numerous emergency events that have significantly damaged society and the economy, the need for emergency decision-making has been manifest recently. It assumes a controllable function when it is critical to limit property and personal catastrophes and lessen their negative consequences on the natural and social course of events. In emergency decision-making problems, the aggregation method is crucial, especially when there are more competing criteria. Based on these factors, we first introduced some basic concepts about SHFSS, and then we introduced some new aggregation operators such as the spherical hesitant fuzzy soft weighted average, spherical hesitant fuzzy soft ordered weighted average, spherical hesitant fuzzy weighted geometric aggregation, spherical hesitant fuzzy soft ordered weighted geometric aggregation, spherical hesitant fuzzy soft hybrid average, and spherical hesitant fuzzy soft hybrid geometric aggregation operator. The characteristics of these operators are also thoroughly covered. Also, an algorithm is developed within the spherical hesitant fuzzy soft environment. Furthermore, we extend our investigation to the Evaluation based on the Distance from Average Solution method in multiple attribute group decision-making with spherical hesitant fuzzy soft averaging operators. And a numerical illustration for "supply of emergency aid in post-flooding the situation" is given to show the accuracy of the mentioned work. Then a comparison between these operators and the EDAS method is also established in order to further highlight the superiority of the established work.

A PROMETHEE based outranking approach for the construction of Fangcang shelter hospital using spherical fuzzy sets

This study mainly aims to develop two effective and practical multi-criteria group decision-making approaches by taking advantage of the ground-breaking theory of PROMETHEE family of outranking methods. The presented variants of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method are acknowledged to address the complex decision-making problems carrying the ambiguous information, expressible in terms of yes, no, abstinence and refusal, owing to the preeminent condition and wider structure of spherical fuzzy sets. Both of the proposed approaches seek help from the Shannon's entropy formula to evaluate the object weights of the decision criteria. The proposed techniques operate by taking into account the deviation between each pair of potential alternatives in accordance to different types of preference functions to determine the preference indices. The proposed technique of spherical fuzzy PROMETHEE I method carefully compares the positive and negative outranking flows of the alternative to get partial rankings. In contrast, the spherical fuzzy PROMETHEE II method has the edge to eliminate the incomparable pair by employing the net outranking flow to derive the final ranking. The application of proposed approaches is explained via a case study in the field of medical concerning the selection of appropriate site to establish Fangcang shelter hospital in Wuhan to treat COVID-19 patients. The convincing comparisons of the proposed methodologies with q-rung orthopair fuzzy PROMETHEE and spherical fuzzy TOPSIS methods are also included to verify the aptitude of the proposed methodology.

Research on emergency material demand based on urgency and satisfaction under public health emergencies

In recent years, the frequent occurrence of public health emergencies has had a significant impact on people's life. The study of emergency logistics has also attracted scholars' attention. Therefore, matching emergency materials' supply and demand quickly, which meets urgency and satisfaction, is the purpose of this paper. This paper used the Metabolism Grey Model (1,1) (GM (1,1)) and the material demand prediction model to predict the number of infections and material demand. Besides, we established a bi-objective optimization model by constructing a profit and loss matrix and a comprehensive utility perception matrix. The results show that the method is helpful in matching the optimal supply and demand decision quickly on the basis of meeting urgency and satisfaction. The method is helpful in improving the fairness of emergency material distribution, which could better protect people's livelihoods.