This paper provides a comprehensive survey of fuzzy-based scheduling algorithms in distributed environments, focusing on grid, cloud, and fog computing. The authors review high-quality articles published between 2005 and June 2023, comparing various fuzzy-based scheduling schemes based on their merits, demerits, evaluation techniques, simulation environments, and important parameters. The study highlights the advantages of using fuzzy logic in decision-making processes due to its low computational complexity and processing power requirements. The paper begins by introducing distributed environments and the scheduling process, followed by a detailed review of fuzzy logic and its applications in distributed systems. It discusses the basic concepts of fuzzy inference systems and the motivations behind using fuzzy theory in schedulers. The paper then explores how fuzzy logic is employed in different aspects of scheduling, such as calculating fitness functions, assigning tasks to fog/cloud nodes, and clustering tasks or resources. Finally, the paper identifies open challenges and promising future directions in fuzzy-based scheduling, emphasizing the need for further research to address the limitations and issues associated with existing scheduling algorithms.This paper provides a comprehensive survey of fuzzy-based scheduling algorithms in distributed environments, focusing on grid, cloud, and fog computing. The authors review high-quality articles published between 2005 and June 2023, comparing various fuzzy-based scheduling schemes based on their merits, demerits, evaluation techniques, simulation environments, and important parameters. The study highlights the advantages of using fuzzy logic in decision-making processes due to its low computational complexity and processing power requirements. The paper begins by introducing distributed environments and the scheduling process, followed by a detailed review of fuzzy logic and its applications in distributed systems. It discusses the basic concepts of fuzzy inference systems and the motivations behind using fuzzy theory in schedulers. The paper then explores how fuzzy logic is employed in different aspects of scheduling, such as calculating fitness functions, assigning tasks to fog/cloud nodes, and clustering tasks or resources. Finally, the paper identifies open challenges and promising future directions in fuzzy-based scheduling, emphasizing the need for further research to address the limitations and issues associated with existing scheduling algorithms.