Akademik Məlumat İdarəetmə Sistemi
Sustainable Cities and Society, vol.116, 2024 (SCI-Expanded, Scopus)
Renewable energy resources are pivotal in addressing global energy challenges and achieving sustainable development goals. In this context, the complex picture fuzzy sets (CPFS) theory provides a robust framework for handling complex and uncertain information. This article presents innovative strategies based on Frank aggregation tools to evaluate and prioritize renewable energy resources. By incorporating the concepts of abstinence value, membership value, and non-membership values in the CPFS framework, the characteristics and capabilities of the CPFS are extended to represent a broader range of information. Specifically, we introduce novel operators such as the CPF Frank weighed average (CPFFWA) and CPF Frank weighed geometric (CPFFWG) operators, effectively handling insufficient and unpredictable information during the aggregation process. Moreover, we explore specialized variants of these operators, such as the CPF Frank order weighed average (CPFFOWA) and CPF Frank order weighed geometric (CPFFOWG) operators, which possess distinct characteristics suitable for specific decision-making scenarios. The proposed methodologies are applied within the framework of multi-attribute group decision-making (MAGDM) to evaluate and identify optimal renewable energy options from a group of alternatives. Through comparative analyses and validation against existing approaches, the advantages and consistency of our developed operators are demonstrated. The findings highlight the effectiveness of the CPF-based Frank aggregation operators in evaluating renewable energy resources, providing decision-makers with a comprehensive and reliable framework for renewable energy planning and decision-making.