Abstract
This review article focuses on the integration of Neutrosophic Set Theory and Extended Fuzzy Set Theory in the context of Linear Programming (LP) problems. Neutrosophic set theory deals with uncertain, imprecise, and indeterminate information, while Extended Fuzzy Set Theory extends the classical fuzzy set theory to handle more complex and nuanced membership degrees. The combination of these two frameworks provides a powerful toolset for modeling and solving LP problems in environments where uncertainty and ambiguity are prevalent. This review aims to analyze and summarize the existing literature on Neutrosophic Linear Programming problems in extended fuzzy environments, exploring the theoretical foundations and practical applications. The review article seeks to contribute to the understanding of these integrated approaches and their potential for addressing decision-making problems under complex and uncertain conditions.
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