Clean energy has become a hot topic worldwide because of the continuous rise in the climate's temperature. Reduced air pollution is only one of the many economic and environmental advantages of clean energy. An effective contractor with experience and knowledge in clean energy projects is always required to handle the complicated process of planning, implementing, and maintaining the new clean energy infrastructure. Contractor selection for renewable energy projects (REPs) is a multi-attribute group decision-making (MAGDM) problem. Linguistic T-spherical fuzzy set (LT-SFS) can be compatible with fuzzier information, and the contractor selection problem also has a lot of fuzzy information, which makes LT-SFS very suitable for contractor selection for REPs. Hence, the present work proposes a MAGDM methodology utilizing a combinative distance-based assessment (CODAS) method within the LT-SF context. For that, the Einstein and Frank t-norm and t-conorm has been used to define new and generalized operational laws for linguistic T-spherical fuzzy numbers. Then, the linguistic T-spherical fuzzy Einstein and linguistic T-spherical fuzzy Frank aggregation operators are proposed to integrate the information data provided by experts. Moreover, the proposed aggregation operators based-CODAS approach is designed to evaluate and rank the available alternatives. A real-life decision problem of selecting the best suitable contractor for a renewable energy project is solved to verify our suggested technique. Moreover, the sensitivity analysis is also carried out by changing the parameter's value to check the consistency of the rank order. Finally, the new model is compared with existing approaches to demonstrate its strength. The comparative analysis shows that the results of the suggested technique are more feasible and beneficial than those of existing approaches.

中文翻译：

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基于语言T球模糊聚合算子的组合距离评估方法及其在多属性群决策中的应用

随着气候气温的持续升高，清洁能源已成为全球范围内的热门话题。减少空气污染只是清洁能源的众多经济和环境优势之一。始终需要一个在清洁能源项目方面具有经验和知识的有效承包商来处理规划、实施和维护新的清洁能源基础设施的复杂过程。可再生能源项目（REP）的承包商选择是一个多属性群体决策（MAGDM）问题。语言T球模糊集（LT-SFS）可以兼容较模糊的信息，承包商选择问题也有大量的模糊信息，这使得LT-SFS非常适合REP的承包商选择。因此，目前的工作提出了一种 MAGDM 方法，在 LT-SF 背景下利用基于组合距离的评估 (CODAS) 方法。为此，爱因斯坦和弗兰克 t-范数和 t-conorm 已被用来定义语言 T 球模糊数的新的广义运算法则。然后，提出语言T球模糊Einstein和语言T球模糊Frank聚合算子来整合专家提供的信息数据。此外，所提出的基于 CODAS 聚合算子的方法旨在评估和排序可用的替代方案。解决了为可再生能源项目选择最合适承包商的现实决策问题，以验证我们建议的技术。此外，还通过改变参数值进行敏感性分析，以检查排序的一致性。最后，将新模型与现有方法进行比较以证明其优势。比较分析表明，该技术的结果比现有方法更可行、更有益。