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A novel artificial bee colony algorithm for numerical function optimization

机译:一种新颖的人工蜂菌落算法,用于数值函数优化

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Artificial Bee Colony (ABC) algorithm is a widely used optimization algorithm. However, it is good in exploration but poor in exploitation. To improve the optimization performance of ABC algorithm, two novel search mechanisms served as the search equations are proposed. Firstly, the improved algorithm integrates the information of previous best solution into the search equation in the onlookers to improve the exploitation. Secondly, the search policy of the scouts is modified, the distance between the optimal and the worst solutions is utilized to replace the worst solution, so as to avoid producing worse solution. The result shows that the proposed algorithm has higher precision and stability compared with other algorithms.
机译:人造蜜蜂菌落(ABC)算法是一种广泛使用的优化算法。然而,它在探索中很好,但剥削差。为了提高ABC算法的优化性能,提出了一种作为搜索方程式的两种新的搜索机制。首先,改进的算法将先前最佳解决方案的信息集成到旁观者中的搜索方程中,以改善剥削。其次,修改了侦察员的搜索策略,利用最佳解决方案与最差解决方案之间的距离来更换最坏的解决方案,以避免产生更糟糕的解决方案。结果表明,与其他算法相比,该算法具有更高的精度和稳定性。

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