The paper by Momin Jamil and Xin-She Yang reviews and compiles a comprehensive set of 175 benchmark functions for unconstrained global optimization problems. These functions are designed to test the performance of optimization algorithms by varying in terms of modality, separability, and valley landscape. The authors emphasize the importance of having a diverse set of functions to accurately evaluate algorithms, as specialized or limited sets can lead to biased results. The paper also discusses the characteristics of test functions, including modality, basins, valleys, separability, and dimensionality, which are crucial for understanding the complexity and difficulty of optimization problems. The benchmark functions are categorized based on these characteristics and are provided with their mathematical formulations, domain constraints, and optimal solutions. This collection aims to serve as a valuable resource for researchers and practitioners in the field of global optimization.The paper by Momin Jamil and Xin-She Yang reviews and compiles a comprehensive set of 175 benchmark functions for unconstrained global optimization problems. These functions are designed to test the performance of optimization algorithms by varying in terms of modality, separability, and valley landscape. The authors emphasize the importance of having a diverse set of functions to accurately evaluate algorithms, as specialized or limited sets can lead to biased results. The paper also discusses the characteristics of test functions, including modality, basins, valleys, separability, and dimensionality, which are crucial for understanding the complexity and difficulty of optimization problems. The benchmark functions are categorized based on these characteristics and are provided with their mathematical formulations, domain constraints, and optimal solutions. This collection aims to serve as a valuable resource for researchers and practitioners in the field of global optimization.