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A Simple and Efficient Artificial Bee Colony Algorithm

机译：一种简单高效的人工蜂群算法

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摘要

Artificial bee colony (ABC) is a new population-based stochastic algorithm which has shown good search abilities on many optimization problems. However, the original ABC shows slow convergence speed during the search process. In order to enhance the performance of ABC, this paper proposes a new artificial bee colony (NABC) algorithm, which modifies the search pattern of both employed and onlooker bees. A solution pool is constructed by storing some best solutions of the current swarm. New candidate solutions are generated by searching the neighborhood of solutions randomly chosen from the solution pool. Experiments are conducted on a set of twelve benchmark functions. Simulation results show that our approach is significantly better or at least comparable to the original ABC and seven other stochastic algorithms.
机译：人工蜂群（ABC）是一种新的基于种群的随机算法，在许多优化问题上显示出良好的搜索能力。但是，原始ABC在搜索过程中显示出较慢的收敛速度。为了提高ABC的性能，本文提出了一种新的人工蜂群算法（NABC），该算法修改了受雇蜂和围观蜂的搜索模式。通过存储当前群集的一些最佳解决方案来构造解决方案池。通过搜索从解决方案池中随机选择的解决方案的邻域来生成新的候选解决方案。实验针对一组十二种基准功能进行。仿真结果表明，我们的方法明显优于或至少与原始ABC和其他七个随机算法相当。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第1期|526315.1-526315.9|共9页
  • 作者

    Yunfeng Xu; Ping Fan; Ling Yuan;

  • 作者单位

    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China,Department of Information Security Engineering, Chinese People's Public Security University, Beijing 100038, China;

    School of Computer Science, Hubei University of Science and Technology, Xianning 437100, China;

    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;

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