Journal Articles
Permanent URI for this collectionhttp://10.0.100.92:4000/handle/123456789/21
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Item Evaluation of sustainable cold chain suppliers using a combined multi-criteria group decision-making framework under fuzzy ZE-numbers(Expert Systems with Applications, 2024-07) Ecer, Fatih; Haseli, Gholamreza; Krishankumar, Raghunathan; Hajiaghaei-Keshteli, MostafaHealth 4.0 actively focuses on cold supply chains (CSCs) due to digital transformation and technological advancements in refrigeration. With the ill effects of climate change and greenhouse gas emissions, countries globally seek sustainable supply chain management. In this context, integrating sustainability with CSCs becomes crucial. Health sectors actively consider CSC for their activities. In this context, to gain potential suppliers for healthcare management, the present work focuses on grading suppliers from the CSC with sustainability factors. Previous related studies on sustainable cold chain supplier selection (CSSS) (i) have not modeled uncertainty effectively, and (ii) have yet to use any approach under fuzzy Z-numbers information. Therefore, this paper developed an integrated framework, including the Logarithm Methodology of Additive Weights (LMAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods based on extended fuzzy Z-numbers. The practicality of the framework is exemplified via a case example within the Indian health sector, and results indicate that job creation, value price, and productivity via renewable resources are the most critical factors. Moreover, regarding the findings, the economic dimension is the foremost pillar for effective selection. Sensitivity and comparison analyses are performed to understand the efficacy of the integrated framework as well. The proposed framework could contribute to the relevant literature due to its capacity to cope with complex decision-making problems and find many application areas in engineering.Item Evaluating smart grid investment drivers and creating effective policies via a fuzzy multi-criteria approach(Renewable and Sustainable Energy Reviews, 2025-02) Dinçer, Hasan; Krishankumar, Raghunathan; Yüksel, Serhat; Ecer, FatihIt is critical to determine which factors impact more smart grid investments and which smart grid investment policy is more suitable for renewable energy projects. Nonetheless, a limited amount of research has focused on this topic, meaning a new study is needed to fill this gap and aid in making decisions under ambiguities. Thus, this research proposes a novel fuzzy group decision-making framework. Twelve drivers are examined through the fuzzy weighted decision-making trial and evaluation laboratory (F–DEMATEL–W) methodology. Subsequently, four smart grid investment policies are ranked using fuzzy weighted aggregated sum product assessment (F–WASPAS). Hence, one of the novelties of this research is the proposal of a robust decision-making tool named F–DEMATEL–W–WASPAS. Other novelties are: (i) the importance of the indicators/criteria is methodically determined by considering pairwise interactions and weights of experts; (ii) both individualistic expert-driven weight vector and cumulative weight vector of indicators are determined; (iii) alternative policies are ranked with minimum decision parameters; (iv) drivers that are crucial for the effectiveness of smart grid investment are determined with their causal relationship, and (v) smart grid investment policies are ranked reliably. The findings demonstrate that cyber security, sufficient legal procedures, and financial viability are the foremost drivers to increase the effectiveness of smart grid investments. Moreover, encouraging sustainable energy production using financial incentives is the foremost policy, followed by exchanging surplus electricity for the system owners. The work may contribute to the ongoing discussion on designing smart grid investment policies for renewable energy projects.