基于混沌局部搜索算子的人工蜂群算法

Artificial bee colony algorithm based on chaos local search operator

在求解函数优化问题时,为了提升人工蜂群算法局部搜索能力,提出了一种新颖的混沌蜂群算法。新算法设计了一种混沌局部搜索算子,并将其嵌入蜂群算法框架中;该算子不仅能够实现在最优食物源周围局部搜索,还能够随着进化代数增加使搜索范围不断缩小。仿真实验结果表明,与人工蜂群算法相比,新算法在Rosenbrock函数上,求解精度和收敛速度明显占优;此外新算法在多模函数Griewank和Rastrigin上,收敛速度明显占优。

In order to improve the ability of Artificial Bee Colony（ABC） algorithm at exploitation,a new Chaos Artificial Bee Colony（CH-ABC） algorithm was proposed for continuous function optimization problems.A new chaotic local search operator was embedded in the framework of the new algorithm.The new operator,whose search radius shrinks with the evolution generation,can do the local search around the best food source.The simulation results show that： compared with those of ABC algorithm,the solution quality and the convergence speed of the new algorithm are better for Rosenbrock and the convergence speed of the new algorithm is better for Griewank and Rastrigin.