2013
DOI: 10.1016/j.apm.2012.08.012
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A grey relational projection method for multi-attribute decision making based on intuitionistic trapezoidal fuzzy number

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Cited by 156 publications
(81 citation statements)
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References 28 publications
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“…Liu and Wu (2012) suggested a new model based on multi-granularity linguistic variables and VIKOR method for assessment of competency of human resources managers. Zhang et al (2013) developed a new decision making analysis method based on grey relational projection. Teng (2014, 2015) presented extended TODIM method with the form of 2-dimension uncertain linguistic variables and the intuitionistic uncertain linguistic variables.…”
Section: Methodsmentioning
confidence: 99%
“…Liu and Wu (2012) suggested a new model based on multi-granularity linguistic variables and VIKOR method for assessment of competency of human resources managers. Zhang et al (2013) developed a new decision making analysis method based on grey relational projection. Teng (2014, 2015) presented extended TODIM method with the form of 2-dimension uncertain linguistic variables and the intuitionistic uncertain linguistic variables.…”
Section: Methodsmentioning
confidence: 99%
“…In contrast, if the index is cost-oriented, the minimum optimal sequence U and the maximum pessimism sequence L should be selected. With respect to the specific evaluation models, we use the traditional grey relationship method to analyze the variation trend in the degree of correlation between variable factors at different time periods for a 4PL supplier's technology index, and the improved grey relationship method to evaluate the comprehensive indexes for several 4PL suppliers [8,9,10]. The following section provides the case numerical study.…”
Section: Determination Methods For Grey Rela-tionship Weight and The Smentioning
confidence: 99%
“…Just as some professionals' query the feasibility of sustainable development, there are three views on the practical application of sustainable development to leisure agriculture, including completely believing that sustainable development is applicable to leisure agriculture, believing that sustainable leisure agriculture with environmental, social, and economic objectives can be jointly executed; secondly, specific thoughts denying the common development of sightseeing and social environments, where the former is perfect. Finally, facing existing challenges, the negative significant impact of sightseeing development is accepted, determines the full necessity of sustainable development, and is devoted to an overall integrated coordination strategy of sightseeing development and environmental protection (Hsu, 2011;Tai et al, 2011;Wei, 2011a;Wei, 2011b;Golmohammadi and Mellat-Parast, 2012;Luo and Wang, 2012;Manzardo et al, 2012;Zhu and Hipel, 2012;Zhang et al, 2013;Wang et al, 2013a;Chang, 2013a;2013b;Wang et al, 2013b;Oztaysi, 2014).…”
Section: Figure-2 Intelligent Digital Content Analysis and Recommendmentioning
confidence: 99%
“…Leisure agriculture and type of operation with sustainable customer value are analyzed by multi-criteria decision making (gray multi-attribute decision making and multi-objective planning). This study uses gray multiattribute decision making to select the optimal implementation plan, and then uses the priority factors, as sorted by the optimal implementation plan, to analyze the most important profit objectives of multi-objective planning according to different situations: the revenue model, cost structure, target unit profit, and developing the constraints (Hsu, 2011;Tai et al, 2011;Wei, 2011a;Wei, 2011b;Golmohammadi and Mellat-Parast, 2012;Luo and Wang, 2012;Manzardo et al, 2012;Zhu and Hipel, 2012;Zhang et al, 2013;Wang et al, 2013a;Chang, 2013a;2013b;Wang et al, 2013b;Oztaysi, 2014). Leisure agriculture is usually commerce and interest oriented, where the cultural aspect of sustainable operation takes cultural protection and popularization as the main implementation objectives; therefore, there are constant conflicts, meaning it is urgent to integrate the leisure agriculture of sustainable customer value with culture.…”
Section: Figure-2 Intelligent Digital Content Analysis and Recommendmentioning
confidence: 99%