An integrated group FWA-ELECTRE III approach based on interval type-2 fuzzy sets for solving the MCDM problems using limit distance mean

Mohamadghasemi, A.; Hadi-Vencheh, A.; Lotfı, Farhad Hosseinzadeh; Khalilzadeh, Mohammad

doi:10.1007/s40747-020-00130-x

Cited by 26 publications

(14 citation statements)

References 97 publications

(111 reference statements)

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“…A MCDM framework was also developed by integrating fuzzy set theory and ELECTRE III, the resulted framework was applied to the material handling equipment evaluation and selection(A. Mohamadghasemi, Hadi-Vencheh, Lotfi, & Khalilzadeh, 2020). To enhance understanding of user preferences with respect to luxury cars, an AHP model embodying various evaluation criteria was configured.…”

Section: Related Workmentioning

confidence: 99%

An integrated ANP-ELECTRE III decision model applied to eco-friendly car selection

Mumani

Magableh

2021

JER is an international, peer-reviewed journal that publishes f

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The number of green energy options in different fields is growing because of the need for reducing energy consumption and eliminating gas emission. One of these options is the use of eco-friendly cars produced by various manufacturers. Given the many available options and conflicting evaluation criteria, evaluation of such options becomes complex, and different multi-criteria decision-making (MCDM) approaches have been used to select the most suitable car in terms of eco-friendly car selection. Previous research has been somewhat limited with respect to consideration of interdependencies between evaluation criteria and multi-levels of preference. This paper proposes a new integrated MCDM approach with the capability for considering interdependent criteria for eco-friendly car evaluation and different levels of preference. An analytic network process (ANP) will be used to evaluate the levels of importance of interdependent criteria, and ELECTRE III will be modeled to include thresholds of preference. The introduced model, based on twenty-eight evaluation criteria, was demonstrated in a case study dealing with five alternative electric and hybrid cars. The results from this model were compared to a traditional decision-making method and better results were obtained from the model. The model can help users make proper decisions regarding their future car options in a comprehensive manner. Sensitivity analysis showed the robustness of the model under different setups.

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Section: Related Workmentioning

confidence: 99%

An integrated ANP-ELECTRE III decision model applied to eco-friendly car selection

Mumani

Magableh

2021

JER is an international, peer-reviewed journal that publishes f

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“…The objective function minimizes the sum of the widths of fuzzy productivity forecasts by considering both LMF and UMF, thereby narrowing both the ranges of LMF and UMF (Figure 4) to maximize the forecasting precision [41]. Constraints (24) and (25) suggest that the membership of an actual value in the corresponding fuzzy forecast should be higher than the satisfaction level (s) based on UMF. X t1 and X t2 are binary variables, as defined in (29).…”

Section: Mbqp Model For Deriving the Values Of Fuzzy Parametersmentioning

confidence: 99%

“…Therefore, a desirable option is to form a narrow interval that contains most of the collected data by excluding extreme cases, as illustrated in Figure 2. To this end, an interval fuzzy number (IFN) [22][23][24] is a viable option. There exist two membership functions in an IFN, one of which is suitable for modeling the inner part of a fuzzy productivity forecast, whereas the other is suitable for modeling the outer part.…”

Section: Introductionmentioning

confidence: 99%

Modeling an Uncertain Productivity Learning Process Using an Interval Fuzzy Methodology

2020

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Existing methods for forecasting the productivity of a factory are subject to a major drawback—the lower and upper bounds of productivity are usually determined by a few extreme cases, which unacceptably widens the productivity range. To address this drawback, an interval fuzzy number (IFN)-based mixed binary quadratic programming (MBQP)–ordered weighted average (OWA) approach is proposed in this study for modeling an uncertain productivity learning process. In the proposed methodology, the productivity range is divided into the inner and outer sections, which correspond to the lower and upper membership functions of an IFN-based fuzzy productivity forecast, respectively. In this manner, all actual values are included in the outer section, whereas most of the values are included within the inner section to fulfill different managerial purposes. According to the percentages of outlier cases, a suitable forecasting strategy can be selected. To derive the values of parameters in the IFN-based fuzzy productivity learning model, an MBQP model is proposed and optimized. Subsequently, according to the selected forecasting strategy, the OWA method is applied to defuzzify a fuzzy productivity forecast. The proposed methodology has been applied to the real case of a dynamic random access memory factory to evaluate its effectiveness. The experimental results indicate that the proposed methodology was superior to several existing methods, especially in terms of mean absolute error, mean absolute percentage error, and root mean square error in evaluating the forecasting accuracy. The forecasting precision achieved using the proposed methodology was also satisfactory.

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“…Hence, authors moved to the fuzzy ELECTRE III method (Leyva-López and Fernández-González, 2003; Li et al , 2007; Montazer et al , 2009; Lupo, 2015), it mentions only the possible membership degree of the given information. The intuitionistic fuzzy ELECTRE III method (Shen et al , 2017; Hashemi et al , 2016; Celik et al , 2016; Mohamadghasemi et al , 2020), represents both possible membership and non- membership degrees of the given information. But these methods are expressing vagueness of the given information.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of national innovation capabilities of OECD countries using trapezoidal interval type-2 fuzzy ELECTRE III method

Geetha

Jeon

2020

DTA

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PurposeFor a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.Design/methodology/approachIn recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.FindingsThis analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.Originality/valueThe authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.

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An integrated group FWA-ELECTRE III approach based on interval type-2 fuzzy sets for solving the MCDM problems using limit distance mean

Cited by 26 publications

References 97 publications

An integrated ANP-ELECTRE III decision model applied to eco-friendly car selection

An integrated ANP-ELECTRE III decision model applied to eco-friendly car selection

Modeling an Uncertain Productivity Learning Process Using an Interval Fuzzy Methodology

Assessment of national innovation capabilities of OECD countries using trapezoidal interval type-2 fuzzy ELECTRE III method

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