全局优化的改进鸡群算法

鸡群算法是一种新颖的群智能算法,模拟鸡群中的等级制度以及觅食行为,相比于传统的智能算法,其展现出了良好的寻优性能。在基本鸡群算法的基础之上,提出了一种改进版鸡群算法（ECSO）,在公鸡位置的更新过程中引入自适应变异策略用于平衡算法迭代后期下降的种群多样性,提升收敛速度;在母鸡移动过程引入偏好随机游动策略来平衡了算法的“开发”与“探索”阶段,增强算法的稳定性;在小鸡位置更新时引入“领导者”策略,减少算法搜索的盲目性。最后,通过测试多组函数,并与基本蝙蝠算法和鸡群算法以及已有改进的鸡群算法进行对比,验证了改进算法的有效性。

Enhanced chicken swarm algorithm for global optimization

The chicken swarm algorithm is a novel swarm intelligence algorithm, which imitating the rank system and foraging behavior in the chicken group and showing a certain advantage over the traditional intelligent algorithm. Based on the chicken swarm algorithm, this paper proposed an improved version of the chicken swarm algorithm (ECSO) , which introducing adaptive mutation strategy for balancing algorithm later decreased diversity of the population and improving the speed of convergence process and introducing random walk strategy preference into hen mobile update process to balance "development" and "exploration" stage to enhance the stability of the algorithm, and which introducing "leader" strategy of updating position of chickens to reduce the blindness of the search algorithm. Finally, the effectiveness of the improved algorithm is verified by comparing the test benchmark functions with the basic bat algorithm and the chicken swarm algorithm and other improved chicken swarm algorithm .