A Crossover Operator Based on Building Blocks Preservation
2023 18th Iberian Conference on Information Systems and Technologies (CISTI)(2023)
摘要
In this study, we propose a novel crossover operator for solving optimization problems in genetic algorithms. Our method preserves existing building blocks in the parent chromosomes, which improves the convergence rate and the quality of the results. We compare the performance of our proposed method with three other crossover operators, including one-point, n-point, and uniform crossovers. We use a set of X test problems from the global optimization literature to evaluate the performance of these four genetic algorithms. To assess the effectiveness of our proposed method, we conduct two types of analysis, including a comparison of the convergence curves and an evaluation of the quality of the results obtained.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要