Fishmeal Supplier Evaluation and Selection for Aquaculture Enterprise Sustainability with a Fuzzy MCDM Approach

Wu, Tung Hsin; Chen, Chia-Hsin; Mao, Ning; Lu, Shih-Tong

doi:10.3390/sym9110286

Cited by 8 publications

(8 citation statements)

References 49 publications

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“…Other practical applications including fuzzy logic that can be mentioned are: the design of a warning system and fire monitoring system for smart buildings [15], modeling pedestrian dynamic behavior [16], choosing the location for power plants [17], supplier evaluation and selection [18], investment decision optimization [19], assessing the commercial viability of technology start-up businesses [20], e-commerce regional cooperation [21], material selection procedures [22], risk assessment [23], cooperative mobile robots' learning [24], and alternatives' evaluation [25], etc. As for the theoretical aspects related to fuzzy logic application with regard to multi-attribute decision making, more can be read in [26][27][28][29][30][31][32][33][34][35][36][37].…”

Section: Symmetry 2019 11 X For Peer Review 3 Of 18mentioning

confidence: 99%

The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy

2019

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This paper develops a Mamdani fuzzy logic system (FLS) that has stochastic fuzzy input variables designed to identify cash-flow deficits in bank lending policies. These deficits do not cover the available cash-flow (CFA) resulting from the company's operating activity. Thus, due to these deficits, solutions must be identified to avoid companies' financial difficulties. The novelty of this paper lies in its using stochastic fuzzy variables, or those categories of variables that are defined by fuzzy sets, characterized by normally distributed density functions specific to random variables, and characterized by fuzzy membership functions. The variation intervals of the stochastic fuzzy variables allow identification of the probabilistic risk situations to which the company is exposed during the crediting period using the Mamdani-type fuzzy logic system. The mechanism of implementing the fuzzy logic system is based on two stages. The first is based on the determination of the cash-flow requirements resulting from loan reimbursement and interest rates. This stage has the role of determining the need for financial resources to cover the liabilities. The second stage is based on the identification of the stochastic fuzzy variables which have a role in influencing the cash flow deficits and the probability values estimation of these variables taking into account probability calculations. Based on these probabilistic values, using the Mamdani fuzzy logic system, estimations are computed for the available cash-flow (the output variable). The estimated values for CFA are then used to detect probability risk situations in which the company will not have enough resources to cover its liabilities to financial creditors. All the FLS calculations refer to future time periods. Testing and simulating the fuzzy controller confirms its functionality.

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Section: Symmetry 2019 11 X For Peer Review 3 Of 18mentioning

confidence: 99%

The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy

2019

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“…While the distance rate of the negative ideal solution of the ith alternative is represented by (Ri-R + / R --R + ) meaning that the majority disagree with the rate of the ith alternative. Generally, v = 0.5 to show that the compromising attitude of evaluation experts where v is the weight of maximum group utility and 1-v is the weight of individual regret [32,33].…”

Section: C1 C2mentioning

confidence: 99%

Decision Support Strategy in Selecting Natural Fiber Materials for Automotive Side-Door Impact Beam Composites

Shaharuzaman¹,

Sapuan²,

Mansor³

et al. 2019

Journal of Renewable Materials

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The enforcement on sustainable design and environmental-friendly products has attracted the interest of researchers and engineers in the context of replacing metals and synthetic fibers with natural based fibers, especially in the automotive industry. However, studies on sustainable natural fiber material selection in the automotive industry are limited. Evaluation for the side-door impact beam was conducted by gathering product design specification from literature which amounted to seven criteria and it was forwarded to ten decision makers with automotive engineering and product design background for evaluation. The weightage required for decision-making was obtained using the Analytic Hierarchy Process (AHP) method based on six criteria. Following this, the best natural fiber materials to be used as reinforcement in polymer composites were selected using the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. The results using both the AHP and VIKOR method showed that kenaf was the best natural fiber for the side-door impact beam composites. The result showed the lowest VIKOR value, QA1 = 0.0000, which was determined to be within the acceptable advantage and acceptable stability conditions. It can be concluded that the application of integrated AHP-VIKOR method resulted in a systematic and justified solution towards the decision-making process.

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“…As mentioned in the discussion in Section 1, in this step, we transform the evaluation information of these indices according to the symmetric linguistic evaluation scale into neutrosophic numbers with truth, indeterminacy, and falsity. Then, we aggregate the neutrosophic numbers by utilizing the single-valued neutrosophic weighted averaging (SVNWA) aggregation operator described by Equation (5). Therefore, the evaluation matrix of R = (r ij ) based on a 25 , a 26 , a 41 , a 42 , a 43 , a 44 , a 51 , a 52 , a 53 , and a 54 is defined, where ψ = (ψ 1 , ψ 2 , .…”

Section: The Evaluation Matrix Of Early Gastric Cancer Surgerymentioning

confidence: 99%

“…Consequently, it is necessary to study and develop a proper approach to select the most appropriate surgical treatment according to the patient's conditions. As the optimum surgical treatment is usually determined by an expert group, surgical treatment selection for early gastric cancer is a group decision-making problem affected by several conflicting factors [5] such as tumor characteristics, surgical situation, surgical outcomes, medical technology, and medical equipment.…”

Section: Introductionmentioning

confidence: 99%

A Novel Selection Model of Surgical Treatments for Early Gastric Cancer Patients Based on Heterogeneous Multicriteria Group Decision-Making

Cheng

et al. 2018

Symmetry

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Gastric cancer results in malignant tumors with high morbidity and mortality, and seriously affects the health and life quality of patients. Early detection and appropriate treatment for early-stage gastric cancer patients are very helpful to reducing the recurrence rate and improving survival rates. Hence, the selection of a suitable surgical treatment is an important part. At present, surgical treatment selection has been researched in numerous studies, but there is no study integrating fuzzy decision-making theory with quantitative analysis, considering the patient's conditions with other relative conditions, and which can handle multisource heterogeneous information at the same time. Hence, this paper proposes a novel selection model of surgical treatments for early gastric cancer based on heterogeneous multiple-criteria group decision-making (MCGDM), which is helpful to selecting the most appropriate surgery in the case of asymmetric information between doctors and patients. Subjective and objective criteria are comprehensively taken into account in the index system of the selection model for early gastric cancer, which combines fuzzy theory with quantitative data analysis. Moreover, the evaluation information obtained from the patient's conditions, the surgery, and the hospital's medical status, etc., including crisp numbers, interval numbers, neutrosophic numbers, and probabilistic linguistic labels, is more complete and real, so the surgical treatment selection is accurate and reliable. Furthermore, the technique for order of preference by similarity to ideal solution (TOPSIS) method is employed to solve the prioritization of early gastric cancer surgical treatments. Finally, an empirical study of surgical treatment selection for early gastric cancer surgery is conducted, and the results of sensitivity analysis and comparative analysis suggest that the proposed selection model of surgical treatments for early gastric cancer patients is reliable and effective.

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Fishmeal Supplier Evaluation and Selection for Aquaculture Enterprise Sustainability with a Fuzzy MCDM Approach

Cited by 8 publications

References 49 publications

The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy

The Development of a Fuzzy Logic System in a Stochastic Environment with Normal Distribution Variables for Cash Flow Deficit Detection in Corporate Loan Policy

Decision Support Strategy in Selecting Natural Fiber Materials for Automotive Side-Door Impact Beam Composites

A Novel Selection Model of Surgical Treatments for Early Gastric Cancer Patients Based on Heterogeneous Multicriteria Group Decision-Making

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