Abstract

Parameters identification of photovoltaic models and engineering problems with constraints are recognized as complex optimization tasks in real-world applications. In this paper, an upgraded variant of Dung Beetle Optimizer (MSDBO) is proposed. MSDBO incorporates three key strategies. Firstly, dynamic population size variation dynamically adjusts the population size to balance global exploration in the early stages and local exploitation in the later stages.

光伏模型参数辨识与带约束的工程问题被认为是实际应用中的复杂优化任务。本文提出多策略增强蜣螂优化器，应用于光伏模型参数辨识与工程优化，取得优越结果。

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