摘要
针对基本萤火虫算法优化多峰函数时求解精度不高和后期收敛较慢的问题,引入萤光因子以自适应调整萤火虫的步长,提出一种自适应步长萤火虫优化算法。通过8个标准测试函数测试,测试结果表明,改进后的自适应步长萤火虫算法比基本萤火虫算法具有较快的寻优速度和较高的寻优精度。
According to the problem that Glowworm Swarm Optimization(GSO) cannot acquire solutions exactly and converge slowly in the later period for solving the multimodal function,an improved GSO algorithm combined with luciferin-factor,which can adaptively adjust step,was proposed.The simulation results show that the improved Self-Adaptive Step Glowworm Swarm Optimization(ASGSO) can search for global optimization more quickly and precisely.
出处
《计算机应用》
CSCD
北大核心
2011年第7期1804-1807,共4页
journal of Computer Applications
基金
广西自然科学基金资助项目(0991086)
关键词
多峰函数
萤火虫优化算法
自适应
步长
萤光因子
multimodal function
Glowworm Swarm Optimization(GSO) algorithm
self-adaptive
step
luciferin-factor