具有双重认知能力的人工蜂群算法及性能分析

针对人工蜂群算法在解决单峰问题时收敛速度过慢而在优化多峰问题时易陷入局部最优值的问题,依据群体动力学原理,引入"自我认知能力"和"社会认知能力"对蜂群觅食时的蜜源搜索策略进行改进,提出了具有双重认知策略的人工蜂群算法。用经典的标准测试函数进行了实验并与其他改进算法进行了比较,结果表明,改进的搜索策略提高了算法的优化能力,优于其他改进的人工蜂群算法。

Improved Artificial Bee Colony Algorithm with Dual Cognitive Abilities and Performance Analysis

Aiming at the problem that artificial bee colong algorithm has slower convergence rate in resolving unimodal problems and is easily trapped into local optimum in optimizing multimodal problems,according to the theory of group dynamics,an improved artificial bee colony algorithm with dual cognitive abilities which improves the search strategies of bees foraging behavior was presented by introducing the self-cognition and social cognition abilities.The experimental results show that the improved search strategies enhance the optimization performance of artificial bee colony algorithm and are superior to others by testing in a set of standard test functions.