摘要
在模拟退火的高斯扰动蝙蝠优化算法(SAGBA)的基础上,结合解决多目标优化问题的算法技术,探讨了2种改进的多目标蝙蝠算法——基于动态加权的SAGBA算法(DWASAGBA)和基于向量估计的SAGBA算法(VESAGBA),并对算法进行了仿真实验.结果表明,SAGBA算法所得到的解集分布均匀,能够得到测试函数较为准确的Pareto曲线.
Combined the SAGBA algorithm with the technology of solving the problem of multi-objective optimization, two kinds of improved multi-objective bat algorithm the SAGBA algorithm based on dynamic weighted (DWASAGBA) and the SAGBA algorithm based on vector estimation(VESAGBA) are discussed. The simulation experiment results show that the solution set distribution is uniform, and can get a relatively accurate Pareto curve,so the SAGBA algorithm is effective in solving multi-objective optimization problems.
出处
《纺织高校基础科学学报》
CAS
2013年第4期537-542,共6页
Basic Sciences Journal of Textile Universities
基金
陕西省软科学基金项目(2012KRM58)
陕西省教育厅自然科学基金项目(12JK0744
11JK0188)
西安工程大学研究生创新基金项目(chx131115)