A Non-Dominated Sorting Evolutionary Algorithm Updating When Required

Lucas R. C. Farias; Abimael J. F. Santos; Matheus R. B. Nobre

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arXiv · 2507.03864

A Non-Dominated Sorting Evolutionary Algorithm Updating When Required

Lucas R. C. Farias·Abimael J. F. Santos·Matheus R. B. Nobre

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Abstract

The NSGA-III algorithm relies on uniformly distributed reference points to promote diversity in many-objective optimization problems. However, this strategy may underperform when facing irregular Pareto fronts, where certain vectors remain unassociated with any optimal solutions. While adaptive schemes such as A-NSGA-III address this issue by dynamically modifying reference points, they may introduce unnecessary complexity in regular scenarios. This paper proposes NSGA-III with Update when Required (NSGA-III-UR), a hybrid algorithm that selectively activates reference vector adaptation based on the estimated regularity of the Pareto front. Experimental results on benchmark suites (DTLZ1-7, IDTLZ1-2) and real-world problems demonstrate that NSGA-III-UR consistently outperforms NSGA-III and A-NSGA-III across diverse problem landscapes.

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Lucas R. C. Farias, Abimael J. F. Santos, Matheus R. B. Nobre. 2025-07-05. A Non-Dominated Sorting Evolutionary Algorithm Updating When Required. https://arxiv.org/abs/2507.03864

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