Maintaining a balance between convergence and diversity is particularly crucial in evolutionary multiobjective optimization. Recently, a novel dominance relation called “strengthened dominance relation” (SDR) is proposed, which outperforms the existing dominance relations in balancing convergence and diversity. In this article, two points that influence the performance of SDR are studied and a new dominance relation, which is mainly based on SDR, is proposed (CSDR). An adaptation strategy is presented to dynamically adjust the dominance relation according to the current generation number. The CSDR is embedded into NSGA-II to substitute the Pareto dominance, labeled as NSGA-II/CSDR. The performance of our proposed method is validated by comparing it with five state-of-the-art algorithms on commonly used benchmark problems. NSGA-II/CSDR outperforms other algorithms in the most test instances considering both convergence and diversity.

中文翻译：

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进化多目标优化的受控强化优势关系

在进化多目标优化中保持收敛和多样性之间的平衡尤为重要。最近，一种新的支配关系被提出，称为“加强支配关系”（SDR），它在平衡收敛性和多样性方面优于现有的支配关系。本文研究了影响 SDR 性能的两点，并提出了一种主要基于 SDR 的新的支配关系（CSDR）。提出了一种适应策略，根据当前代数动态调整优势关系。CSDR 嵌入到 NSGA-II 中以替代 Pareto 优势，标记为 NSGA-II/CSDR。我们提出的方法的性能通过在常用基准问题上与五种最先进的算法进行比较来验证。