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A levy flight-based hybrid artificial bee colony algorithm for solving numerical optimization problems

机译:一种求解数字优化问题的基于征航的混合人工蜂群算法

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An artificial bee colony (ABC) algorithm is one of numerous swarm intelligence algorithms that employs the foraging behavior of honeybee colonies. To improve the convergence performance and search speed of finding the best solution using this approach, we propose a levy flight-based hybrid ABC algorithm in this paper. To evaluate the performance of the standard and proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation 2013 test suite. The proposed ABC algorithm demonstrated competitive performance on these optimization problems as compared to standard ABC, differential evolution, and particle swarm optimization algorithms with dimension sizes of 10, 30, and 50, respectively.
机译:人工蜂群(ABC)算法是采用蜂群觅食行为的众多群智能算法之一。为了提高收敛性能和使用这种方法寻找最佳解决方案的搜索速度,我们提出了一种基于征费飞行的混合ABC算法。为了评估标准和提出的ABC算法的性能,我们基于IEEE Con​​gress on Evolution Computation 2013测试套件实施了数值优化问题。与标准ABC,差分进化和尺寸分别为10、30和50的粒子群优化算法相比,拟议的ABC算法在这些优化问题上展示了竞争性能。

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