scholarly journals The Optimum Output Quantity for Different Competitive Behaviors under a Fuzzy Decision Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Hong-Xia Sun ◽  
Yu Li ◽  
Feng Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Model ◽  
Market Demand ◽  
Fuzzy Decision ◽  
Proposed Model ◽  
Decision Environment ◽  
Fuzzy Parameter ◽  
Output Quantity ◽  
Total Market ◽  
Optimum Output

Due to the uncertainty of information and complexity of decision-making environment, the optimum output quantity is studied under a fuzzy decision environment. Firstly, the triangular intuitionistic fuzzy model is proposed. Secondly, the optimum output quantity is discussed for four patterns to market structure. Thirdly, the effect of fuzzy parameter on optimum output quantity and total market demand is discussed. Finally, a numerical example is given to illustrate the concrete application of the proposed model.

scholarly journals FMADM: YAGER MODEL IN FUZZY DECISION MAKING

2018 ◽  
Vol 12 (1) ◽  
pp. 1
Author(s):  
Kisworo Kisworo
Keyword(s):  
Decision Making ◽  
Standard Form ◽  
Team Work ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making ◽  
Fuzzy Decision ◽  
Multi Objective ◽  
Decisionmaking Process ◽  
Decision Environment

This paper presents Yager model, i.e. standard form of Fuzzy Multi-Atributte Decision Making (FMADM) in fuzzy decision environment. Simulasion of this model would be performed under scope of fuzzy decisionmaking process to show its existence. As academics, researchers, and practitioners know on it, besides theFMADM, so is there Fuzzy Multi-Objective Decision Making (FMODM) at where the both has their same derivation, e.i. Fuzzy Multi-Criteria Decision Making (FMCDM). Related to the matter, significant value that could be represented then gives contribution to team work-oriented principal of decision makers.Keywords: Yager Model, FMADM, FMODM, FMCDM, fuzzy decision-making.

scholarly journals Retreat: Fuzzy Multi-Criteria Decision Making Based on Pros And Cons

2019 ◽  
Vol 8 (2) ◽  
pp. 6072-6079
Keyword(s):  
Decision Making ◽  
Final Decision ◽  
Multi Criteria Decision Making ◽  
Fuzzy Decision ◽  
Fuzzy Aggregation ◽  
Life Issues ◽  
Decision Environment ◽  
Pros And Cons ◽  
Interval Type

We introduce a new fuzzy multi-criteria decision making method using interval type-2 pentagonal fuzzy numbers. We propose to incorporate pros and cons of an issue to arrive at better decision. The necessary concepts and terminologies are defined. The proposed decision method consists of three stages. We use a prioritized interval type-2 pentagonal fuzzy aggregation operator to arrive at a tentative decision in the second stage. We use the existing concept of synthesis value and define a new suitable formula in order to accommodate fuzzy decision environment with pros and cons of an issue. A formula to combine the de-fuzzified pro-value and con-value of an alternative is proposed and the same is used to rank the alternatives. We further introduce concept of consolation score to align the final decision with the gut level of a decision maker. The fuzzy concepts such as fuzzy relations and fuzzy trace theory are employed to arrive at consolation score. This newly proposed fuzzy multi-criteria decision making method is a comprehensive and complete approach to a decision problem particularly concerning life-issues.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

scholarly journals Neuro-Fuzzy Transformation with Minimize Entropy Principle to Create New Features for Particulate Matter Prediction

2021 ◽  
Vol 11 (14) ◽  
pp. 6590
Author(s):  
Krittakom Srijiranon ◽  
Narissara Eiamkanitchat
Keyword(s):  
Particulate Matter ◽  
Fuzzy Model ◽  
Original Data ◽  
Northern Region ◽  
National Standard ◽  
Minimum Entropy ◽  
Fuzzy Transformation ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Entropy Principle

Air pollution is a major global issue. In Thailand, this issue continues to increase every year, similar to other countries, especially during the dry season in the northern region. In this period, particulate matter with aerodynamic diameters smaller than 10 and 2.5 micrometers, known as PM10 and PM2.5, are important pollutants, most of which exceed the national standard levels, the so-called Thailand air quality index (T-AQI). Therefore, this study created a prediction model to classify T-AQI calculated from both types of PM. The neuro-fuzzy model with a minimum entropy principle model is proposed to transform the original data into new informative features. The processes in this model are able to discover appropriate separation points of the trapezoidal membership function by applying the minimum entropy principle. The membership value of the fuzzy section is then passed to the neural section to create a new data feature, the PM level, for each hour of the day. Finally, as an analytical process to obtain new knowledge, predictive models are created using new data features for better classification results. Various experiments were utilized to find an appropriate structure with high prediction accuracy. The results of the proposed model were favorable for predicting both types of PM up to three hours in advance. The proposed model can help people who are planning short-term outdoor activities.

scholarly journals An MCDM Model for Sustainable Decision-Making in Municipal Residential Buildings Facilities Management

2021 ◽  
Vol 13 (5) ◽  
pp. 2820
Author(s):  
Eglė Klumbytė ◽  
Raimondas Bliūdžius ◽  
Milena Medineckienė ◽  
Paris A. Fokaides
Keyword(s):  
Decision Making ◽  
Residential Buildings ◽  
Global Changes ◽  
Facilities Management ◽  
Informed Decision Making ◽  
Soviet Republic ◽  
Building Management ◽  
Proposed Model ◽  
Product Assessment ◽  
The Eu

Measuring and monitoring sustainability plays an essential role in impact assessment of global changes and development. Multi-criteria decision-making (MCDM) represents a reliable and adequate technique for assessing sustainability, especially in the field of municipal buildings management, where numerous parameters and criteria are involved. This study presents an MCDM model for the sustainable decision-making, tailored to municipal residential buildings facilities management. The main outcome of this research concerned normalized and weighted decision-making matrixes, based on the complex proportion assessment (COPRAS) and weighted aggregated sum product assessment (WASPAS) methods, applied for ranking investment alternatives related to the management of the buildings. The delivered model was applied to 20 municipal buildings of Kaunas city municipality, located in Lithuania, which an EU member state employing practices and regulations in accordance with the EU acquis, as well as a former Soviet Republic. The proposed model aspires to enhance sustainability practices in the management of municipal buildings and to demonstrate a solid tool that will allow informed decision-making in the building management sector.

Dual hesitant fuzzy decision making in optimization models

2021 ◽  
Vol 154 ◽  
pp. 107103
Author(s):  
Fanyong Meng ◽  
Jie Tang ◽  
Witold Pedrycz
Keyword(s):  
Decision Making ◽  
Optimization Models ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision

Determining the safety culture in a gun factory in Turkey: A fuzzy approach

2020 ◽  
pp. 1-11
Author(s):  
Gökçen A. Çiftçioğlu ◽  
Mehmet A. N. Kadırgan ◽  
Ahmet Eşiyok
Keyword(s):  
Safety Culture ◽  
Fuzzy Inference ◽  
Fuzzy Model ◽  
Self Awareness ◽  
Inference System ◽  
Five Factors ◽  
Initial Questionnaire ◽  
Proposed Model ◽  
Assessment Questionnaire

Safety culture is a very complex phenomenon due to its intangible nature. It is tough to measure and express it with numerical values, as there is no simple indicator to measure it. This paper presents a fuzzy inference system that measures the safety culture. First of all, a safety culture assessment questionnaire is developed by utilizing related literature. The initial questionnaire had 29 items. The questionnaire is applied to 259 employees within the gun manufacturing factory. After making an exploratory factor analysis, the questionnaire is based on five factors with 25 items. The safety culture indicators are defined as; safety follow-up audit reporting, employees’ self-awareness, operational safety commitment, management’s safety commitment, safety orientedness. Normality, reliability, and correlation analysis are performed. Then a fuzzy model is constructed with five inputs and one output. The inputs are the five factors mentioned above, and the output generated is the safety culture result, which is between 0-1. The presented fuzzy model produces reliable results indicating the safety culture level from the employees’ eyes. Beyond exploring the employees’ safety culture, the proposed model can easily be understood by the practitioners from various sectors. Furthermore, the model is straightforward to customize for various fields of industry.

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