摘要
针对免疫克隆选择优化算法晚期收敛速度慢的不足,通过引入搜索空间自适应缩放的思想,提出一种新的空间自适应免疫克隆选择优化算法(SAIS)。算法利用不完全演化搜索优化解的分布特性,以精英个体为中心收缩搜索空间,并采用空间扩张机制帮助算法跳出局部最优。通过对高维基准测试函数实验表明,SAIS能显著提高收敛速度和优化解的质量。
To improve the convergence speed in standard immune clonal selection algorithm(AIS),a new space self-adaptive immune clonal selection optimization algorithm(SAIS) was presented by introducing the thoughts of space contraction and expansion.The algorithm used distribute characters of solution in non-complete evolution process to contract searching space,so as to accelerate convergence speed.Meanwhile it jumped away from the local optimum by expanding searching space.Four high dimension Benchmark optimization...
出处
《计算机应用》
CSCD
北大核心
2009年第2期561-564,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(50778109)
关键词
自适应
空间收缩
空间扩张
免疫克隆选择优化
抗体
抗原
亲和度
self-adaptive
space contraction
space expansion
immune clonal selection optimization
antibody
antigen
affinity
