摘要
针对烟花算法(FA)寻优过程中粒子间信息交流少、对最优点位置不在原点和原点附近的目标函数求解能力差的缺点,提出带有引力搜索算子的烟花算法(FAGSO).算子利用粒子间相互引力作用对粒子维度信息进行改善,以提高算法的优化性能.6个标准和增加位置偏移测试函数的仿真结果表明,FAGSO相比于FA、粒子群算法和引力搜索算法,在寻优速度和寻优精度方面有更好的优化性能.
For the problems that the individuals including fireworks and sparks are not well-informed in the process of searching optimum, and the algorithm yields a poor result when being applied on shifted functions whose optimum are not at the origin or near the origin,a hybrid fireworks algorithm with the gravitational search operator（FAGSO） is proposed. The operator improves the particles dimension information through the gravity between individuals. Simulation experiments are conducted on 6 standard and shifted benchmark functions. Results show that the hybrid algorithm displays better performance compared to the fireworks algorithm（FA）, the particle swarm optimization（PSO） algorithm and the gravitational search algorithm（GSA）.
出处
《控制与决策》
EI
CSCD
北大核心
2016年第10期1853-1859,共7页
Control and Decision
基金
国家自然科学基金项目(61271384
61275155)
中央高校基本科研业务费专项基金项目(JUSRP51510)
关键词
烟花算法
引力搜索
偏移函数
函数优化
全局寻优
fireworks algorithm
gravitational search
shifted function
function optimization
global optimization
