An intuitionistic fuzzy decision support system for COVID-19 lockdown relaxation protocols in India

Devi, S. Aicevarya; Felix, A.; Narayanamoorthy, Samayan; Ahmadian, Ali; Balaenu, Dumitru

doi:10.1016/j.compeleceng.2022.108166

Cited by 19 publications

(5 citation statements)

References 22 publications

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“…, 2023), risk assessment (Chen et al. , 2023), modeling lockdown relaxation protocols (Aicevarya Devi et al. , 2022; Ocampo and Yamagishi, 2020), green SC management (Govindan et al.…”

Section: Methodsmentioning

confidence: 99%

“…IF-DEMATEL has found many applications in research field, for example, water security (Abdullah et al, 2023), risk assessment (Chen et al, 2023), modeling lockdown relaxation protocols (Aicevarya Devi et al, 2022;Ocampo and Yamagishi, 2020), green SC management (Govindan et al, 2015;Haiyun et al, 2021), personnel selection (Kilic et al, 2020), power generation project (Wu et al, 2020), solid waste management (Abdullah et al, 2019), etc. A brief description of the methodology is given as follows.…”

Section: Intuitionistic Fuzzy Dematelmentioning

confidence: 99%

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Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Sharma,

Kumar,

Arora

2023

BPMJ

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PurposeThe pharmaceutical industry faces multiple risks that adversely affect its performance. Within these risks, some dependencies have been observed, which help in streamlining the mitigation efforts. Therefore, the present work identifies and categorizes various risks/sub-risks in cause–effect groups, considering uncertainty in the decision-making process.Design/methodology/approachAn extensive literature review and experts' opinions were utilized to identify and finalize the risks faced by the pharmaceutical industry. For further analysis, data collection was done using a questionnaire focusing on finalized risks. Based on the data, the causal relation under uncertainty between various risks/sub-risks was identified using a multi-criteria decision making (MCDM) technique, i.e. intuitionistic fuzzy DEMATEL, in a pairwise manner.FindingsThe results show that the three most prominent risk categories are operational, demand/customer/market and financial. Also, out of the seven main risks, only supplier and operational are categorized within the effect group and the rest, i.e. financial, demand, logistics, political and technology within the cause group. The sub-risks within each category have also been categorized into cause–effect groups. The mitigation of cause group risks will help in economize the financial resources and improve the performance and resilience of the industry.Originality/valueThere is insufficient research on identifying the causality among the pharmaceutical industry risks. Additionally, an extensive discussion on the identified cause–effect groups is also missing in the literature. Therefore, in this work, efforts have been made to determine the prominent risks for the Indian pharmaceutical industry that will be helpful for channelizing the resources to mitigate risks for a resilient industry.

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“…, 2023), risk assessment (Chen et al. , 2023), modeling lockdown relaxation protocols (Aicevarya Devi et al. , 2022; Ocampo and Yamagishi, 2020), green SC management (Govindan et al.…”

Section: Methodsmentioning

confidence: 99%

Section: Intuitionistic Fuzzy Dematelmentioning

confidence: 99%

Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Sharma,

Kumar,

Arora

2023

BPMJ

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“…Among the decision making models, MCDM is one of the most widely used decision methodologies involving both quantitative and qualitative factors in which the ranking of the alternatives are found in relation with various criteria. This technique includes several well-known methods like TOPSIS, 5 VIKOR, 6 AHP, 7,8 COPRAS, 9 Entropy, 10 WASPAS, 11 DEMATEL, [12][13][14] MAUT, 15 etc. Thus, MCDM methods were used in the fuzzy field to select the appropriate robot for a particular application.…”

Section: Introductionmentioning

confidence: 99%

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Sampathkumar

Felix

Kaabar

et al. 2023

Advances in Mechanical Engineering

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Manufacturing robots are used for industrial purposes. Robots used for manufacturing purpose have the power to create products from raw materials and are capable of operating endlessly even in lights-out situations for continuous production. Manufacturing robots can be used in applications like arc welding, spot welding, materials handling, machine tending, painting, machine cutting and so on. Selecting a robot for a given application is complex. However, robot selection is used in selecting a suitable robot for the preferred output with specific application ability. In recent years, many authors used multi-criteria decision-making methods to select a robot that meets the need. This study presents a hybrid model by integrating complex proportional assessment (COPRAS) with the weighted aggregates sum product assessment (WASPAS) methods in intuitionistic dense fuzzy set to select a manufacturing robot for a particular application. Intuitionistic dense fuzzy entropy is used in calculating the weights for the criteria and intuitionistic dense fuzzy COPRAS and WASPAS are used in ranking the best alternatives where in the optimum types of robots are obtained. Here, intuitionistic dense fuzzy sets are used as it is capable of dealing with the intangible factors while selecting a robot. On the basis of the manufacturing robot selection, two comparisons are given. First, the results are compared with various [Formula: see text] values between 0 and 1 and second the results are compared with the fuzzy set, intuitionistic fuzzy set and the dense fuzzy set to show the effectiveness of the proposed methodology with the intuitionistic dense fuzzy set.

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“… 2021 Crisp Flood vulnerability in Kashkan Watershed, Iran To assess flood vulnerability and interdependency among criteria Identified critical factors and their interrelationships Deva and Felix 2021 Bipolar fuzzy Choosing preferable mobile networks To determine interdependence among selected networks Identified preferable network Devi et al. 2022 Intuitionistic fuzzy COVID-19 lockdown relaxation protocols in India To examine efficiency of protocols Identified critical factors and their impacts Singh et al. 2022 Fuzzy E-waste collection policy in India To analyze critical success factors Segregated factors into cause-and-effect groups Gani et al.…”

Section: Introductionmentioning

confidence: 99%

“…Then, Akram, 2011 adopted these concepts into fuzzy graphs and invented the idea of bipolar fuzzy graphs (BFG), where the weightage of vertices and edges is a BFS. In recent studies, the concepts of BFS and BFG are utilized multi-attribute decision-making systems to analyze various problems (Akram and Waseem, 2018), (Akram et al, 2017), (Deva and Felix, 2021), (Devi et al, 2022), (Kang et al, 2022). Atanassov, 1986 paved the way to an intuitionistic fuzzy set (IFS) by considering the element's belonging, nonbelongingness and hesitancy grades.…”

Section: Introductionmentioning

confidence: 99%

Bipolar intuitionistic fuzzy graph based decision-making model to identify flood vulnerable region

Nithyanandham,

Augustin,

Narayanamoorthy

et al. 2023

Environ Sci Pollut Res

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Bipolar intuitionistic fuzzy graphs (BIFG) are an extension of fuzzy graphs that can effectively capture uncertain or imprecise information in various applications. In graph theory, the covering, matching, and domination problems are benchmark concepts applied to various domains. These concepts may not be defined precisely using a crisp graph when the vertices and edges are more uncertain. Therefore, this study defines the covering, matching and domination concepts in bipolar intuitionistic fuzzy graphs (BIFG) using effective edges with certain important results. To define these concepts when the effective edges are absent, some novel approaches are discussed. To illustrate the domination concepts, the applications in disaster management and location selection problems are discussed. Further, a BIFG-based decision-making model is designed to identify the flood-vulnerable zones in Chennai, where the city’s most and least vulnerable zones are identified. From the proposed model, Kodambakkam ( ) is the most susceptible zone in Chennai. Finally, a comparative analysis is done with the existing techniques to show the efficiency of the model.

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An intuitionistic fuzzy decision support system for COVID-19 lockdown relaxation protocols in India

Cited by 19 publications

References 22 publications

Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

Analyzing pharmaceutical industry risks under uncertainty for performance improvement: an Indian scenario

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Bipolar intuitionistic fuzzy graph based decision-making model to identify flood vulnerable region

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