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首页> 外文期刊>Applied mathematics and computation >A modified artificial bee colony algorithm based on converge-onlookers approach for global optimization
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A modified artificial bee colony algorithm based on converge-onlookers approach for global optimization

机译：改进的基于会聚视角的人工蜂群算法全局优化

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摘要

Artificial bee colony (ABC) is a novel biological-inspired optimization algorithm, having the advantage of less control parameters, strong global optimization ability and easy to implement. It has received significant interest from researchers studying in different fields since it was invented. However, there are still some problems in ABC algorithm, such as slow to converge, easily get trapped in local optima and hard to find the best solution from all feasible solutions, and so on. In this work, we propose a modified algorithm called convergeonlookers ABC (COABC) algorithm. In order to improve the exploitation, a new solution search equation in the onlooker stage by applying the best solution of the previous iteration to guide the search of new candidate solutions was presented. In COABC algorithm, the roulette wheel selection mechanism based on nectar amounts of each food source was saved. Moreover, all employed bees to update not only once in each iteration, which helps improving both solution quality and convergence rate of ABC algorithm remarkably. The experimental results tested on numerical benchmark functions show that the COABC algorithm has excellent solution quality and convergence characteristics comparing to basic ABC algorithm and performs better than the state-of-art algorithm in some problems. The optimization result in solving the practical problem demonstrates the COABC is a prospect method and can be used in the engineering field.
机译：人工蜂群（ABC）是一种新颖的生物启发式优化算法，具有控制参数少，全局优化能力强，易于实现的优点。自发明以来，它就受到了研究不同领域的研究人员的极大兴趣。然而，ABC算法仍然存在一些问题，例如收敛速度慢，容易陷入局部最优以及难以从所有可行解中找到最佳解，等等。在这项工作中，我们提出了一种改进的算法，称为convergeonlookers ABC（COABC）算法。为了提高开发效率，提出了一个在旁观者阶段的新的搜索方程式，该方程通过应用先前迭代的最佳解来指导新候选解的搜索。在COABC算法中，节省了基于每种食物来源的花蜜量的轮盘赌选择机制。而且，所有采用的蜜蜂在每次迭代中不仅更新一次，这有助于显着提高解决方案质量和ABC算法的收敛速度。在数值基准函数上测试的实验结果表明，与基本的ABC算法相比，COABC算法具有出色的求解质量和收敛特性，并且在某些问题上的性能优于最新的算法。解决实际问题的优化结果表明，COABC是一种有前途的方法，可用于工程领域。

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