Sustainable supplier selection (SSS) is recognized as a prime aim in supply chain because of its impression on profitability, adorability, and agility of the organization. This work introduces a multi-phase intuitionistic fuzzy preference-based model with which decision experts are authorized to choose the suitable supplier using the sustainability "triple bottom line (TBL)" attributes. To solve this issue, an intuitionistic fuzzy gained and lost dominance score (IF-GLDS) approach is proposed using the developed IF-entropy. To make better use of experts' knowledge and fully represent the uncertain information, the evaluations of SSS are characterized in the form of intuitionistic fuzzy set (IFS). To better distinguish fuzziness of IFSs, new entropy for assessing criteria weights is proposed with the help of an improved score function. By considering the developed entropy and improved score function, a weight-determining process for considered criterion is presented. A case study concerning the iron and steel industry in India for assessing and ranking the SSS is taken to demonstrate the practicability of the developed model. The efficacy of the developed model is certified with the comparison by diverse extant models.
Citation: Ibrahim M. Hezam, Pratibha Rani, Arunodaya Raj Mishra, Ahmad Alshamrani. An intuitionistic fuzzy entropy-based gained and lost dominance score decision-making method to select and assess sustainable supplier selection[J]. AIMS Mathematics, 2023, 8(5): 12009-12039. doi: 10.3934/math.2023606
Sustainable supplier selection (SSS) is recognized as a prime aim in supply chain because of its impression on profitability, adorability, and agility of the organization. This work introduces a multi-phase intuitionistic fuzzy preference-based model with which decision experts are authorized to choose the suitable supplier using the sustainability "triple bottom line (TBL)" attributes. To solve this issue, an intuitionistic fuzzy gained and lost dominance score (IF-GLDS) approach is proposed using the developed IF-entropy. To make better use of experts' knowledge and fully represent the uncertain information, the evaluations of SSS are characterized in the form of intuitionistic fuzzy set (IFS). To better distinguish fuzziness of IFSs, new entropy for assessing criteria weights is proposed with the help of an improved score function. By considering the developed entropy and improved score function, a weight-determining process for considered criterion is presented. A case study concerning the iron and steel industry in India for assessing and ranking the SSS is taken to demonstrate the practicability of the developed model. The efficacy of the developed model is certified with the comparison by diverse extant models.
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Ibrahim M. Hezam, Pratibha Rani, Arunodaya Raj Mishra, Ahmad Alshamrani. An intuitionistic fuzzy entropy-based gained and lost dominance score decision-making method to select and assess sustainable supplier selection[J]. AIMS Mathematics, 2023, 8(5): 12009-12039. doi: 10.3934/math.2023606
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