Multiple Criteria Decision Making Based on Probabilistic Interval-Valued Hesitant Fuzzy Sets by Using LP Methodology

Sindhu, Muhammad Sarwar; Rashid, Tabasam; Kashif, Agha; Guirao, Juan Luis García

doi:10.1155/2019/1527612

Cited by 18 publications

(15 citation statements)

References 64 publications

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“…Much of future research was directed toward locating and precisely developing an imitation on the parts of the brain and psychology which is responsible for decisionmaking [24]. By imitating the brain in specific aspects, research will be propelled forward, and it will be assured that brain-inspired decision-making can become a truly useful technology [27]. Currently with the beginning stages of use, for example in the financial sector to solve complicated problems, it is necessary to ensure there is much more research available for users [20].…”

Section: Brain-inspired Decision-making For Businessmentioning

confidence: 99%

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Alexander¹,

Wang²

2020

JBMS

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Brain science and brain-inspired artificial intelligence have the potential for strengthening business and management. Brain-inspired artificial intelligence (AI) uses principles of brain science to build algorithms and AI systems with human-like intelligence. Some concepts (e.g., cognition, inference, memory, and intelligence) and principles of brain science are introduced in this paper. The research progress in several topics are also presented that include brain-inspired artificial intelligence and brain-inspired computing, project management and brain-inspired management, the integration of brain science into leadership (especially crisis leadership), and brain-inspired decision-making for business. Future research and trends in some topics are introduced.

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Section: Brain-inspired Decision-making For Businessmentioning

confidence: 99%

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Alexander¹,

Wang²

2020

JBMS

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“…Data sets, which include substantial uncertain information, demonstrate an academic challenge. In ( Zadeh, 1965) introduced the notion of fuzzy sets to exhibit subjective vagueness and uncertainty (Sindhu et al, 2019). Fuzzy sets have created to deal with the vagueness or ambiguity directly.…”

Section: Introductionmentioning

confidence: 99%

Topsi̇s Yöntemi̇ İle Ortodonti̇k Tedari̇kçi̇ Seçi̇mi̇

Erdebilli

Güneşli

Şahin

2021

Mühendislik Bilimleri Ve Tasarım Dergisi

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Dental supplier selection is a process that allows companies to choose their suppliers correctly in the light of evaluations. Choosing the right dental suppliers is an important factor both for the efficiency of dental treatment and handling an impressive supply chain. Dental supplier selection is a multi-criterion group decision-making (MCDM) problem that contains many different criterion about the decision-makers generally ambiguous information. TOPSIS method integrated intuitionistic fuzzy set is used in this study. Real-life problems include many unpredictability and defects. Experts are involved in assigning the weights of the criterion in this study. Linear programming (LP) methodology has applied for the ranking of these weights of criterion. Then, the LP methodology is carried out and it was ensured that the appropriate orthodontic bracket suppliers were selected. This is a specific multi-criterion decision making problem. The study was followed together with the sensitivity analyses of the results. At the end of the study, it is foreseen that with the right selection of suppliers, The competitive power of companies in the market and end user satisfaction will increase.

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“…Various experts utilized LP [1,2,8,13,16] in MCDM in different fields. Recently, Sindhu et al [14] implemented the LP methodology with extended TOPSIS for picture fuzzy sets.…”

Section: Introductionmentioning

confidence: 99%

Multiple criteria decision making based on bipolar picture fuzzy sets and extended TOPSIS

Sindhu¹,

Ahsan²,

Rafiq³

et al. 2020

J. Math. Computer Sci.

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The notion of bipolar fuzzy sets (B p FSs) has got much attention from the experts or decision-makers (DMs). B p FSs have ample information in the form of two degrees called the positive belonging degree (P v BD) and a negative belonging degree (N v BD). In this article, we introduced the concept of bipolar picture fuzzy sets (BP c FSs) by connecting the concepts of B p FSs and picture fuzzy sets (P c FSs). Firstly, we presented the concept, operational rules, score, and accuracy functions of BP c FSs. Secondly, a distance measure is formulated for the BP c FSs and then implemented for the extension of TOPSIS. Thirdly, a multiple criteria decision making (MCDM) model is proposed to handle the uncertain MCDM problems. Lastly, a practical example related to the sum of money's investment is exemplified to validate and effectiveness of the proposed model.

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Multiple Criteria Decision Making Based on Probabilistic Interval-Valued Hesitant Fuzzy Sets by Using LP Methodology

Cited by 18 publications

References 64 publications

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Brain Science, Brain-inspired Artificial Intelligence, and Applications in Business and Management

Topsi̇s Yöntemi̇ İle Ortodonti̇k Tedari̇kçi̇ Seçi̇mi̇

Multiple criteria decision making based on bipolar picture fuzzy sets and extended TOPSIS

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