7 research outputs found
Hybrid Hesitant Fuzzy Multi-Criteria Decision Making Method: A Symmetric Analysis of the Selection of the Best Water Distribution System
Every country’s influence and livelihood is centered on that country’s water source. Therefore, many studies are being conducted worldwide to improve and sustain water resources. In this research paper, we have selected and researched the water scheme for groundwater recharge and drinking water supply of drought prone areas. The water project is aimed at connecting the drought prone areas of the three districts of Tamil Nadu to filling up the ponds in their respective villages and raising the ground water level and meeting the drinking water requirement. We have chosen a multi-criteria decision method to select the best alternative in a complex situation. When reviewing the implementation of this water project, many experts and people who will benefit from this project may have some hesitation and ambiguity in their suggestion on choosing the best water distribution system.We believe that the benefits of this project can be fully availed of if we choose a water distribution system. Our contribution in this article is to choose the best water distribution system for this project by use of our proposed multi-criteria decision making (MCDM) methods, hesitant fuzzy standard deviation with multi-objective optimization method by ratio analysis (HFSDV-MOORA), hesitant fuzzy standard deviation with technique, for order preference by similarity to an ideal solution (HFSDV-TOPSIS) and hesitant fuzzy standard deviation with VIsekriterijumsko Kompromisno Rangiranje (HFSDV-VIKOR), which will provide the best solution for improving the water resource for the drought-prone areas of three districts. Finally, we have identified and compared the correlation coefficient between proposed methods. As a result of the study, it has been found that the best water supply system is closed concrete pipes laid along agricultural land through the rural areas
Selection of suitable biomass conservation process techniques: a versatile approach to normal wiggly interval-valued hesitant fuzzy set using multi-criteria decision making
Abstract A country that relies on developing industrialization and GDP requires a lot of energy. Biomass is emerging as one of the possible renewable energy resources that may be used to generate energy. Through the proper channels, such as chemical, biochemical, and thermochemical processes, it can be turned into electricity. In the context of India, the potential sources of biomass can be broken down into agricultural waste, tanning waste, sewage, vegetable waste, food, meat waste, and liquor waste. Each form of biomass energy so extracted has advantages and downsides, so determining which one is best is crucial to reaping the most benefits. The selection of biomass conversion methods is especially significant since it requires a careful study of multiple factors, which can be aided by fuzzy multi-criteria decision-making (MCDM) models. This paper proposes the normal wiggly interval-valued hesitant fuzzy-based decision-making trial and evaluation laboratory model (DEMATEL) and the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE) for assessing the problem of determining a workable biomass production technique. The proposed framework is used to assess the production processes under consideration based on parameters such as fuel cost, technical cost, environmental safety, and C O 2 emission levels. Bioethanol has been developed as a viable industrial option due to its low carbon footprint and environmental viability. Furthermore, the superiority of the suggested model is demonstrated by comparing the results to other current methodologies. According to comparative study, the suggested framework might be developed to handle complex scenarios with many variables
Intuitionistic fuzzy MAUT-BW Delphi method for medication service robot selection during COVID-19
Coronavirus Disease 2019 (COVID-19), a new illness caused by a novel coronavirus, a member of the corona family of viruses, is currently posing a threat to all people, and it has become a significant challenge for healthcare organizations. Robotics are used among other strategies, to lower COVID’s fatality and spread rates globally. The robot resembles the human body in shape and is a programmable mechanical device. As COVID is a highly contagious disease, the treatment for the critical stage COVID patients is decided to regulate through medication service robots (MSR). The use of service robots diminishes the spread of infection and human error and prevents frontline healthcare workers from exposing themselves to direct contact with the COVID illness. The selection of the most appropriate robot among different alternatives may be complex. So, there is a need for some mathematical tools for proper selection. Therefore, this study design the MAUT-BW Delphi method to analyze the selection of MSR for treating COVID patients using integrated fuzzy MCDM methods, and these alternatives are ranked by influencing criteria. The trapezoidal intuitionistic fuzzy numbers are beneficial and efficient for expressing vague information and are defuzzified using a novel algorithm called converting trapezoidal intuitionistic fuzzy numbers into crisp scores (CTrIFCS). The most suitable criteria are selected through the fuzzy Delphi method (FDM), and the selected criteria are weighted using the simplified best–worst method (SBWM). The performance between the alternatives and criteria is scrutinized under the multi-attribute utility theory (MAUT) method. Moreover, to assess the effectiveness of the proposed method, sensitivity and comparative analyses are conducted with the existing defuzzification techniques and distance measures. This study also adopt the idea of a correlation test to compare the performance of different defuzzification methods
A Distinctive Symmetric Analyzation of Improving Air Quality Using Multi-Criteria Decision Making Method under Uncertainty Conditions
This world has a wide range of technologies and possibilities that are available to control air pollution. Still, finding the best solution to control the contamination of the air without having any impact on humans is a complicated task. This proposal helps to improve the air quality using the multi-criteria decision making method. The decision to improve air quality is a challenging problem with today’s technology and environmental development level. The multi-criteria decision making method is quite often faced with conditions of uncertainty, which can be tackled by employing fuzzy set theory. In this paper, based on an objective weighting method (CCSD), we explore the improved fuzzy MULTIMOORA approach. We use the classical Interval-Valued Triangular Fuzzy Numbers (IVTFNs), viz. the symmetric lower and upper triangular numbers, as the basis. The triangular fuzzy number is identified by the triplets; the lowest, the most promising, and the highest possible values, symmetric with respect to the most promising value. When the lower and upper membership functions are equated to one, we get the normalized interval-valued triangular fuzzy numbers, which consist of symmetric intervals. We evaluate five alternatives among the four criteria using an improved MULTIMOORA method and select the best method for improving air quality in Tamil Nadu, India. Finally, a numerical example is illustrated to show the efficiency of the proposed method
An augmented fuzzy decision support system to analyse compatible cosmetic face masks for various complexions
Jeon, Jeonghwan/0000-0002-7750-3402Beauty face masks (BFM) are becoming increasingly popular among both men and women since they provide quick refreshment and nurture the skin. Given the wide range of skin types and the chemicals used in their formulation, it can be difficult to find a product that not only complements the skin type but is also free of potentially harmful ingredients that could endanger the consumer's health. When dealing with ambiguous situations, the multi-attribute decision making (MADM) approach combined with fuzzy set theory is more effective. Type-2 fuzzy sets (T2FS) provide greater flexibility in dealing with uncertainty in real-world issues since they are characterised by a main and secondary membership function. In this research, we present the innovative idea of type-2 linear diophantine fuzzy set (T2LDFS) as an intriguing tool for capturing expert reluctance about an issue. For analysing the discussed problem, a hybrid fuzzy VIKOR enhanced with the proposed fuzzy logic is suggested. A sensitivity and comparative analysis is carried out to establish the validity of the recommended approach.National Research Foundation of Korea (NRF) [2019R1A2C1090655]; National Research Foundation of Korea (NRF) - Korean government (MSIT)This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1A2C1090655)
The COVID-19 Vaccine Preference for Youngsters Using PROMETHEE-II in the IFSS Environment
Extensive decision-making during the vaccine preparation period is unpredictable. An account of the severity of the disease, the younger people with COVID-19 comorbidities and other chronic diseases are also at a higher risk of the COVID-19 pandemic. In this research article, the preference ranking structure for the COVID-19 vaccine is recommended for young people who have been exposed to the effects of certain chronic diseases. Multiple Criteria Decision-Making (MCDM) approach effectively handles this vague information. Furthermore, with the support of the Intuitionistic Fuzzy Soft Set (IFSS), the entries under the new extension of the Preference Ranking Organization Method for Enrichment Evaluation-II (PROMETHEE-II) is suggested for Preference Ranking Structure. The concept of intuitionistic fuzzy soft sets is parametric in nature. IFSS suggests how to exploit an intuitionistic ambiguous input from a decision-maker to make up for any shortcomings in the information provided by the decider. The weight of the inputs is calculated under the Intuitionistic Fuzzy Weighted Average (IFWA) operator, the Simply Weighted Intuitionistic Fuzzy Average (SWIFA) operator, and the Simply Intuitionistic Fuzzy Average (SIFA) operator. An Extended PROMETHEE-based ranking, outranking approach is used, and the resultant are recommended under the lexicographic order. Its sustainability and feasibility are explored for three distinct priority structures and the possibilities of the approach. To demonstrate the all-encompassing intuitionistic fuzzy PROMETHEE approach, a practical application regarding COVID-19 severity in patients is given, and then it is compared to other existing approaches to further explain its feasibility, and the sensitivity of the preference structure is examined according to the criteria
Analysis of Vaccine efficacy during the COVID-19 pandemic period using CSF-ELECTRE-I approach
COVID-19 vaccinations have been shown to be safe, efficacious, and life-saving. They, like other vaccines, do not entirely protect everyone who receives them, and no one knows how effectively they can prevent people from spreading the virus to others or whether the booster dosage is dangerous to some vulnerable people. So, in addition to getting vaccinated, we must continue with additional efforts to combat the pandemic. Quantitatively, the pragmatic, appropriate, and phenomenal mechanism of the complex spherical fuzzy set enhances the decision-making efficacy and the ordering quality of the ELECTRE I method to include a profitable and optimal approach for MAGDM. In the CSF environment, critically ill patients are investigated systematically using a pairwise comparison based ELECTRE-I technique. In this paper, we improve the precision of the CSF-based ELECTRE-I approach to an unique score function. The suggested approach’s comparability is examined with techniques that should provide equal importance to the alternatives, and the presented score function’s reliability is validated using the existing score function with the two cases
