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Modified Artificial Bee Colony Algorithm for Reactive Power Optimization

机译:用于无功优化的改进的人工蜂菌落算法

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Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.
机译:实施以解决各种优化问题的生物启发算法(偏见)已显示出现有希望的结果在这一严重复杂的现实世界中非常重要。人造蜜蜂殖民地(ABC)算法,与其他优化算法相比,一种偏差表明了巨大的结果。本文提出了一种新的修改ABC算法,称为JA-ABC3,旨在增强收敛速度并避免过早收敛。已经在十种常用的基准函数上模拟了所提出的算法。它的性能也与其他现有的ABC变体进行了比较。为了证明其稳健的适用性,已经测试了所提出的算法以解决无功功率优化问题。结果表明,该算法对其他现有ABC变体具有卓越的性能。 GABC,BABC1,BABC2,BSFABC DAN IABC在收敛速度方面。此外,所提出的算法还表明了解决无功优化问题的卓越性能。

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