| Abstract [eng] |
This paper explores the influence of random number generation methods on the efficiency of optimization algorithms. It delves into the impact of different generators on algorithm performance, emphasizing the need to understand their properties and how they affect optimization results. The research also discusses the application of the Kolmogorov-Smirnov test to evaluate the quality of random number generators and presents an analysis of various test functions to assess algorithm reliability. Additionally, it compares different random number generators and their precision in generating values, providing insights into their suitability for practical applications and future research. |
